[ { "key": "872NMNEF", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/872NMNEF", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/872NMNEF", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Di Marco et al.", "parsedDate": "2011", "numChildren": 1 }, "data": { "key": "872NMNEF", "version": 1, "itemType": "conferencePaper", "title": "RoboEarth Action Recipe Execution", "creators": [ { "creatorType": "author", "firstName": "D.", "lastName": "Di Marco" }, { "creatorType": "author", "firstName": "M.", "lastName": "Tenorth" }, { "creatorType": "author", "firstName": "K.", "lastName": "Häussermann" }, { "creatorType": "author", "firstName": "O.", "lastName": "Zweigle" }, { "creatorType": "author", "firstName": "P.", "lastName": "Levi" } ], "abstractNote": "", "proceedingsTitle": "", "conferenceName": "", "publisher": "", "place": "", "date": "2011", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "", "series": "", "seriesNumber": "", "DOI": "", "ISBN": "", "citationKey": "", "url": "http://ias.cs.tum.edu/_media/spezial/bib/ias12execution.pdf", "accessDate": "2012-09-26T11:08:28Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Google Scholar", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [ "XV5XAC9H" ], "relations": {}, "dateAdded": "2012-09-26T11:08:28Z", "dateModified": "2012-09-26T11:12:33Z" } }, { "key": "5JZDWCSZ", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/5JZDWCSZ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/5JZDWCSZ", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/91105/items/872NMNEF", "type": "application/json" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } } }, "data": { "key": "5JZDWCSZ", "version": 1, "parentItem": "872NMNEF", "itemType": "attachment", "linkMode": "linked_url", "title": "Full Text", "accessDate": "2012-09-26T11:08:28Z", "url": "http://ias.cs.tum.edu/_media/spezial/bib/ias12execution.pdf", "note": "", "contentType": "application/pdf", "charset": "", "tags": [], "relations": {}, "dateAdded": "2012-09-26T11:08:28Z", "dateModified": "2012-09-26T11:08:28Z" } }, { "key": "VF39JNNJ", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/VF39JNNJ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/VF39JNNJ", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Fox", "numChildren": 0 }, "data": { "key": "VF39JNNJ", "version": 1, "itemType": "computerProgram", "title": "PDDL+", "creators": [ { "creatorType": "programmer", "firstName": "Maria", "lastName": "Fox" } ], "abstractNote": "In this paper we present PDDL+, a planning domain description language for modelling mixed discrete-continuous planning domains. We describe the syntax and modelling style of PDDL+, showing that the language makes convenient the modelling of complex time-dependent effects. We provide a formal semantics for PDDL+ by mapping planning instances into constructs of hybrid automata. Using the syntax of HAs as our semantic model we construct a semantic mapping to labelled transition systems to complete the formal interpretation of PDDL+ planning instances.\nAn advantage of building a mapping from PDDL+ to HA theory is that it forms a bridge between the Planning and Real Time Systems research communities. One consequence is that we can expect to make use of some of the theoretical properties of HAs. For example, for a restricted class of HAs the Reachability problem (which is equivalent to Plan Existence) is decidable.\n\nPDDL+ provides an alternative to the continuous durative action model of PDDL2.1, adding a more flexible and robust model of time-dependent behaviour.", "seriesTitle": "", "versionNumber": "", "date": "", "system": "", "company": "", "place": "", "programmingLanguage": "", "rights": "", "citationKey": "", "url": "http://www.cs.cmu.edu/afs/cs/project/jair/pub/volume27/fox06a-html/Main.html", "accessDate": "", "DOI": "", "ISBN": "", "archive": "", "archiveLocation": "", "libraryCatalog": "", "callNumber": "", "shortTitle": "", "extra": "", "tags": [ { "tag": "hybrid automata" }, { "tag": "mixed discrete-continuous planning" } ], "collections": [ "TTVAAZAJ" ], "relations": {}, "dateAdded": "2012-09-26T11:03:44Z", "dateModified": "2012-09-26T11:03:44Z" } }, { "key": "24R92ER4", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/24R92ER4", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/24R92ER4", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "24R92ER4", "version": 1, "itemType": "computerProgram", "title": "PARA", "creators": [], "abstractNote": "This project examines planning and plan execution mechanisms for human-robot collaboration. When a person and a robot work on a joint task, they must coordinate their actions and the robot must behave in a way that is comfortable and understandable for the person.\n\nOne aspect of this work is plan-based action selection that reacts adaptively to human actions, while keeping to a goal-directed plan. \n\nAnother focus in this project lies on the execution of actions, in particular the navigation. In a collaboration with LAAS-CNRS we work human-aware navigation methods for highly dynamic siutations.", "seriesTitle": "", "versionNumber": "", "date": "", "system": "", "company": "", "place": "", "programmingLanguage": "", "rights": "", "citationKey": "", "url": "", "accessDate": "", "DOI": "", "ISBN": "", "archive": "", "archiveLocation": "", "libraryCatalog": "", "callNumber": "", "shortTitle": "", "extra": "", "tags": [ { "tag": "human robot coordination" }, { "tag": "robot assistance planner" } ], "collections": [ "TTVAAZAJ" ], "relations": {}, "dateAdded": "2012-09-26T11:03:44Z", "dateModified": "2012-09-26T11:03:44Z" } }, { "key": "CNXTH2CZ", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/CNXTH2CZ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/CNXTH2CZ", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Mosenlechner", "numChildren": 0 }, "data": { "key": "CNXTH2CZ", "version": 1, "itemType": "computerProgram", "title": "CRAM", "creators": [ { "creatorType": "programmer", "firstName": "Lorenz", "lastName": "Mosenlechner" } ], "abstractNote": "Cognitive Robot Abstract Machine", "seriesTitle": "", "versionNumber": "", "date": "", "system": "", "company": "", "place": "", "programmingLanguage": "", "rights": "", "citationKey": "", "url": "http://ias.in.tum.de/research/cram", "accessDate": "", "DOI": "", "ISBN": "", "archive": "", "archiveLocation": "", "libraryCatalog": "", "callNumber": "", "shortTitle": "", "extra": "", "tags": [], "collections": [ "TTVAAZAJ" ], "relations": {}, "dateAdded": "2012-09-26T11:03:44Z", "dateModified": "2012-09-26T11:03:44Z" } }, { "key": "QCEW2SP3", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/QCEW2SP3", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/QCEW2SP3", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Kirsch", "numChildren": 0 }, "data": { "key": "QCEW2SP3", "version": 1, "itemType": "computerProgram", "title": "RoLL", "creators": [ { "creatorType": "programmer", "firstName": "Alexandra", "lastName": "Kirsch" } ], "abstractNote": "For planning in the domain of autonomous robots, abstraction of state and actions is indispensable. This abstraction however comes at the cost of suboptimal execution, because relevant information is ignored. A solution is to maintain abstractions for planning, but to fill\n\nin precise information on the level of execution. To do\n\nso, the control program needs models of its own behavior. These models, as well as the control routines themselves, should be learned automatically. Unfortunately,\n\nthe performance of learned routines often drags substantially behind those of programmed ones, at least for complex, interacting, and dynamically changing tasks. In our\n\nopinion this is not due to a poor performance of learning\n\nalgorithms, but to the insufficient integration of learning into control languages. We develop the robot control\n\nand plan language RoLL, which provides mechanisms\n\nfor representing state variables, goals and actions, and\n\nintegrating learning into the controller", "seriesTitle": "", "versionNumber": "", "date": "", "system": "", "company": "", "place": "", "programmingLanguage": "", "rights": "", "citationKey": "", "url": "", "accessDate": "", "DOI": "", "ISBN": "", "archive": "", "archiveLocation": "", "libraryCatalog": "", "callNumber": "", "shortTitle": "", "extra": "", "tags": [ { "tag": "behavior modeling" }, { "tag": "integrated learning" }, { "tag": "robot learning language" } ], "collections": [ "TTVAAZAJ" ], "relations": {}, "dateAdded": "2012-09-26T11:03:44Z", "dateModified": "2012-09-26T11:03:44Z" } }, { "key": "T3ZMKVIV", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/T3ZMKVIV", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/T3ZMKVIV", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Tenorth", "numChildren": 0 }, "data": { "key": "T3ZMKVIV", "version": 1, "itemType": "computerProgram", "title": "KnowRob", "creators": [ { "creatorType": "programmer", "firstName": "Moritz", "lastName": "Tenorth" } ], "abstractNote": "Knowledge processing for robots", "seriesTitle": "", "versionNumber": "", "date": "", "system": "", "company": "", "place": "", "programmingLanguage": "", "rights": "", "citationKey": "", "url": "http://ias.in.tum.de/research/knowledge", "accessDate": "", "DOI": "", "ISBN": "", "archive": "", "archiveLocation": "", "libraryCatalog": "", "callNumber": "", "shortTitle": "", "extra": "", "tags": [ { "tag": "knowledge representation" }, { "tag": "object ontology" }, { "tag": "reasoning" } ], "collections": [ "TTVAAZAJ" ], "relations": {}, "dateAdded": "2012-09-26T11:03:44Z", "dateModified": "2012-09-26T11:03:44Z" } }, { "key": "GB8KCQB9", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/GB8KCQB9", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/GB8KCQB9", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Mosenlechner", "numChildren": 0 }, "data": { "key": "GB8KCQB9", "version": 1, "itemType": "computerProgram", "title": "Cogito", "creators": [ { "creatorType": "programmer", "firstName": "Lorenz", "lastName": "Mosenlechner" } ], "abstractNote": "Plan-based Control of Robotic Agents", "seriesTitle": "", "versionNumber": "", "date": "", "system": "", "company": "", "place": "", "programmingLanguage": "", "rights": "", "citationKey": "", "url": "http://ias.in.tum.de/research/cogito", "accessDate": "", "DOI": "", "ISBN": "", "archive": "", "archiveLocation": "", "libraryCatalog": "", "callNumber": "", "shortTitle": "", "extra": "", "tags": [ { "tag": "reactive behavior" }, { "tag": "transformational planning" } ], "collections": [ "TTVAAZAJ" ], "relations": {}, "dateAdded": "2012-09-26T11:03:44Z", "dateModified": "2012-09-26T11:03:44Z" } }, { "key": "MU3WBZ7U", "version": 2, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/MU3WBZ7U", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/MU3WBZ7U", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Tenorth et al.", "parsedDate": "2010-12-06", "numChildren": 0 }, "data": { "key": "MU3WBZ7U", "version": 2, "itemType": "conferencePaper", "title": "KNOWROB-MAP - knowledge-linked semantic object maps", "creators": [ { "creatorType": "author", "firstName": "M.", "lastName": "Tenorth" }, { "creatorType": "author", "firstName": "L.", "lastName": "Kunze" }, { "creatorType": "author", "firstName": "D.", "lastName": "Jain" }, { "creatorType": "author", "firstName": "M.", "lastName": "Beetz" } ], "abstractNote": "Autonomous household robots are supposed to accomplish complex tasks like cleaning the dishes which involve both navigation and manipulation within the environment. For navigation, spatial information is mostly sufficient, but manipulation tasks raise the demand for deeper knowledge about objects, such as their types, their functions, or the way how they can be used. We present KNOWROB-MAP, a system for building environment models for robots by combining spatial information about objects in the environment with encyclopedic knowledge about the types and properties of objects, with common-sense knowledge describing what the objects can be used for, and with knowledge derived from observations of human activities by learning statistical relational models. In this paper, we describe the concept and implementation of KNOWROB-MAP and present several examples demonstrating the range of information the system can provide to autonomous robots.", "proceedingsTitle": "2010 10th IEEE-RAS International Conference on Humanoid Robots (Humanoids)", "conferenceName": "2010 10th IEEE-RAS International Conference on Humanoid Robots (Humanoids)", "publisher": "IEEE", "place": "", "date": "6-8 Dec. 2010", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "430-435", "series": "", "seriesNumber": "", "DOI": "10.1109/ICHR.2010.5686350", "ISBN": "978-1-4244-8688-5", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Containers", "type": 1 }, { "tag": "Data structures", "type": 1 }, { "tag": "KNOWROB-MAP", "type": 1 }, { "tag": "Knowledge based systems", "type": 1 }, { "tag": "Knowledge engineering", "type": 1 }, { "tag": "Knowledge representation", "type": 1 }, { "tag": "Robot sensing systems", "type": 1 }, { "tag": "Semantics", "type": 1 }, { "tag": "Service robots", "type": 1 }, { "tag": "Statistical analysis", "type": 1 }, { "tag": "autonomous household robots", "type": 1 }, { "tag": "common-sense knowledge", "type": 1 }, { "tag": "encyclopaedias", "type": 1 }, { "tag": "encyclopedic knowledge", "type": 1 }, { "tag": "knowledge-linked semantic object maps", "type": 1 }, { "tag": "manipulation tasks", "type": 1 }, { "tag": "mobile robots", "type": 1 }, { "tag": "statistical relational models", "type": 1 } ], "collections": [ "SSAEUX6T" ], "relations": {}, "dateAdded": "2012-09-26T11:00:31Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "AZITV5GV", "version": 2, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/AZITV5GV", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/AZITV5GV", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Tenorth and Beetz", "parsedDate": "2009-10-10", "numChildren": 0 }, "data": { "key": "AZITV5GV", "version": 2, "itemType": "conferencePaper", "title": "KNOWROB — knowledge processing for autonomous personal robots", "creators": [ { "creatorType": "author", "firstName": "M.", "lastName": "Tenorth" }, { "creatorType": "author", "firstName": "M.", "lastName": "Beetz" } ], "abstractNote": "Knowledge processing is an essential technique for enabling autonomous robots to do the right thing to the right object in the right way. Using knowledge processing the robots can achieve more flexible and general behavior and better performance. While knowledge representation and reasoning has been a well-established research field in artificial intelligence for several decades, little work has been done to design and realize knowledge processing mechanisms for the use in the context of robotic control. In this paper, we report on KNOWROB, a knowledge processing system particularly designed for autonomous personal robots. KNOWROB is a first-order knowledge representation based on description logics that provides specific mechanisms and tools for action-centered representation, for the automated acquisition of grounded concepts through observation and experience, for reasoning about and managing uncertainty, and for fast inference - knowledge processing features that are particularly necessary for autonomous robot control.", "proceedingsTitle": "IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009. IROS 2009", "conferenceName": "IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009. IROS 2009", "publisher": "IEEE", "place": "", "date": "10-15 Oct. 2009", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "4261-4266", "series": "", "seriesNumber": "", "DOI": "10.1109/IROS.2009.5354602", "ISBN": "978-1-4244-3803-7", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Artificial intelligence", "type": 1 }, { "tag": "Automatic control", "type": 1 }, { "tag": "Intelligent robots", "type": 1 }, { "tag": "Knowledge management", "type": 1 }, { "tag": "Knowledge representation", "type": 1 }, { "tag": "Logic", "type": 1 }, { "tag": "Process design", "type": 1 }, { "tag": "Robot control", "type": 1 }, { "tag": "Robotics and automation", "type": 1 }, { "tag": "Uncertainty", "type": 1 }, { "tag": "autonomous personal robots", "type": 1 }, { "tag": "description logics", "type": 1 }, { "tag": "knowledge processing system", "type": 1 }, { "tag": "knowledge reasoning", "type": 1 } ], "collections": [ "SSAEUX6T" ], "relations": {}, "dateAdded": "2012-09-26T11:00:31Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "46PG3QRV", "version": 2, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/46PG3QRV", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/46PG3QRV", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Dongyeop Kang et al.", "parsedDate": "2009-02-15", "numChildren": 0 }, "data": { "key": "46PG3QRV", "version": 2, "itemType": "conferencePaper", "title": "Automatically learning robot domain ontology from collective knowledge for home service robots", "creators": [ { "creatorType": "author", "firstName": "", "lastName": "Dongyeop Kang" }, { "creatorType": "author", "firstName": "", "lastName": "Eugene Seo" }, { "creatorType": "author", "firstName": "", "lastName": "Sookyung Kim" }, { "creatorType": "author", "firstName": "", "lastName": "Ho-Jin Choi" } ], "abstractNote": "Today, for enabling intelligent decision and high accuracy of recognition in service robots, many researchers supplement robot's knowledge model using the additional knowledge. However, the construction of the knowledge requiring much effort and domain experts fully depends on man power by few people. Thus, this paper proposes a fully automated process of acquiring domain knowledge and representing them to efficient and semantically abundant structure. Thus, we investigate the characteristics of OMICS as preceding case study for collective knowledge in robot domain, and describe the automated process of conversion of such collective knowledge to robot domain ontology. Also, we suggest dynamic semantic distribution method to solve appropriate generalization of relation problem. Finally, we evaluate the efficiency and semantic of our structure for the ontology compared to other knowledge bases for robots.", "proceedingsTitle": "11th International Conference on Advanced Communication Technology, 2009. ICACT 2009", "conferenceName": "11th International Conference on Advanced Communication Technology, 2009. ICACT 2009", "publisher": "IEEE", "place": "", "date": "15-18 Feb. 2009", "eventPlace": "", "volume": "03", "issue": "", "numberOfVolumes": "", "pages": "1766-1771", "series": "", "seriesNumber": "", "DOI": "", "ISBN": "978-89-5519-138-7", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Cognitive robotics", "type": 1 }, { "tag": "Concrete", "type": 1 }, { "tag": "Electronic mail", "type": 1 }, { "tag": "Intelligent robots", "type": 1 }, { "tag": "Large-scale systems", "type": 1 }, { "tag": "OMICS", "type": 1 }, { "tag": "Ontologies", "type": 1 }, { "tag": "Ontology", "type": 1 }, { "tag": "Robotics and automation", "type": 1 }, { "tag": "Service robots", "type": 1 }, { "tag": "Web services", "type": 1 }, { "tag": "Wikipedia", "type": 1 }, { "tag": "collective knowledge", "type": 1 }, { "tag": "dynamic semantic distribution method", "type": 1 }, { "tag": "home service robots", "type": 1 }, { "tag": "learning robot domain ontology", "type": 1 }, { "tag": "ontologies (artificial intelligence)", "type": 1 }, { "tag": "ontology learning", "type": 1 } ], "collections": [ "SSAEUX6T" ], "relations": {}, "dateAdded": "2012-09-26T11:00:31Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "43R7QEF6", "version": 2, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/43R7QEF6", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/43R7QEF6", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Pettersson et al.", "parsedDate": "2007-08", "numChildren": 0 }, "data": { "key": "43R7QEF6", "version": 2, "itemType": "journalArticle", "title": "Model-Free Execution Monitoring in Behavior-Based Robotics", "creators": [ { "creatorType": "author", "firstName": "O.", "lastName": "Pettersson" }, { "creatorType": "author", "firstName": "L.", "lastName": "Karlsson" }, { "creatorType": "author", "firstName": "A.", "lastName": "Saffiotti" } ], "abstractNote": "In the near future, autonomous mobile robots are expected to help humans by performing service tasks in many different areas, including personal assistance, transportation, cleaning, mining, or agriculture. In order to manage these tasks in a changing and partially unpredictable environment without the aid of humans, the robot must have the ability to plan its actions and to execute them robustly and safely. The robot must also have the ability to detect when the execution does not proceed as planned and to correctly identify the causes of the failure. An execution monitoring system allows the robot to detect and classify these failures. Most current approaches to execution monitoring in robotics are based on the idea of predicting the outcomes of the robot's actions by using some sort of predictive model and comparing the predicted outcomes with the observed ones. In contrary, this paper explores the use of model-free approaches to execution monitoring, that is, approaches that do not use predictive models. In this paper, we show that pattern recognition techniques can be applied to realize model-free execution monitoring by classifying observed behavioral patterns into normal or faulty execution. We investigate the use of several such techniques and verify their utility in a number of experiments involving the navigation of a mobile robot in indoor environments.", "publicationTitle": "IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics", "publisher": "", "place": "", "date": "Aug. 2007", "volume": "37", "issue": "4", "section": "", "partNumber": "", "partTitle": "", "pages": "890-901", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1109/TSMCB.2007.895359", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "1083-4419", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Agriculture", "type": 1 }, { "tag": "Algorithms", "type": 1 }, { "tag": "Artificial intelligence", "type": 1 }, { "tag": "Cleaning", "type": 1 }, { "tag": "Computer Simulation", "type": 1 }, { "tag": "Condition monitoring", "type": 1 }, { "tag": "Decision Support Techniques", "type": 1 }, { "tag": "Environmental management", "type": 1 }, { "tag": "Equipment Failure Analysis", "type": 1 }, { "tag": "Fault diagnosis", "type": 1 }, { "tag": "Humans", "type": 1 }, { "tag": "Models, Theoretical", "type": 1 }, { "tag": "Motion", "type": 1 }, { "tag": "Pattern Recognition, Automated", "type": 1 }, { "tag": "Pattern recognition", "type": 1 }, { "tag": "Predictive models", "type": 1 }, { "tag": "Robustness", "type": 1 }, { "tag": "Service robots", "type": 1 }, { "tag": "Transportation", "type": 1 }, { "tag": "autonomous mobile robots", "type": 1 }, { "tag": "behavior-based robotics", "type": 1 }, { "tag": "computerised monitoring", "type": 1 }, { "tag": "faulty execution", "type": 1 }, { "tag": "mobile robots", "type": 1 }, { "tag": "model-free execution monitoring", "type": 1 }, { "tag": "neural networks", "type": 1 }, { "tag": "pattern recognition techniques", "type": 1 }, { "tag": "predictive control", "type": 1 }, { "tag": "predictive model", "type": 1 }, { "tag": "robot programming", "type": 1 }, { "tag": "robotics", "type": 1 }, { "tag": "service tasks", "type": 1 } ], "collections": [ "TS4QIKP6" ], "relations": {}, "dateAdded": "2012-09-26T11:00:14Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "BWB75BU3", "version": 2, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/BWB75BU3", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/BWB75BU3", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Camarinha-Matos et al.", "parsedDate": "1994-05-08", "numChildren": 0 }, "data": { "key": "BWB75BU3", "version": 2, "itemType": "conferencePaper", "title": "Execution monitoring in assembly with learning capabilities", "creators": [ { "creatorType": "author", "firstName": "L. M", "lastName": "Camarinha-Matos" }, { "creatorType": "author", "firstName": "L.", "lastName": "Seabra Lopes" }, { "creatorType": "author", "firstName": "J.", "lastName": "Barata" } ], "abstractNote": "A generic architecture for execution supervision of robotic assembly tasks is presented. This architecture provides, at different levels of abstraction, functions for dispatching actions, monitoring their execution, and diagnosing and recovering from failures. Modeling execution failures through taxonomies and causal networks plays a central role in diagnosis and recovery. A discussion on the process of acquisition of such monitoring knowledge is made. Through the use of machine learning techniques, the supervision architecture will be given capabilities for improving its performance over time. Preliminary results of applying machine learning in this area are presented and planned extensions discussed", "proceedingsTitle": ", 1994 IEEE International Conference on Robotics and Automation, 1994. Proceedings", "conferenceName": ", 1994 IEEE International Conference on Robotics and Automation, 1994. Proceedings", "publisher": "IEEE", "place": "", "date": "8-13 May 1994", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "272-279 vol.1", "series": "", "seriesNumber": "", "DOI": "10.1109/ROBOT.1994.350978", "ISBN": "0-8186-5330-2", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Condition monitoring", "type": 1 }, { "tag": "Dispatching", "type": 1 }, { "tag": "Machine learning", "type": 1 }, { "tag": "Manufacturing", "type": 1 }, { "tag": "Process planning", "type": 1 }, { "tag": "Production planning", "type": 1 }, { "tag": "Robotic assembly", "type": 1 }, { "tag": "Service robots", "type": 1 }, { "tag": "Strategic planning", "type": 1 }, { "tag": "Taxonomy", "type": 1 }, { "tag": "assembling", "type": 1 }, { "tag": "causal networks", "type": 1 }, { "tag": "computer aided production planning", "type": 1 }, { "tag": "execution failures", "type": 1 }, { "tag": "execution monitoring", "type": 1 }, { "tag": "execution supervision", "type": 1 }, { "tag": "failures diagnosis", "type": 1 }, { "tag": "generic architecture", "type": 1 }, { "tag": "industrial robots", "type": 1 }, { "tag": "knowledge acquisition", "type": 1 }, { "tag": "learning (artificial intelligence)", "type": 1 }, { "tag": "learning capabilities", "type": 1 }, { "tag": "machine learning techniques", "type": 1 }, { "tag": "recovery", "type": 1 }, { "tag": "robotic assembly tasks", "type": 1 }, { "tag": "supervision architecture", "type": 1 } ], "collections": [ "TS4QIKP6" ], "relations": {}, "dateAdded": "2012-09-26T11:00:14Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "3479BPFR", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/3479BPFR", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/3479BPFR", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Galindo et al.", "parsedDate": "2008-06", "numChildren": 0 }, "data": { "key": "3479BPFR", "version": 1, "itemType": "journalArticle", "title": "Multihierarchical Interactive Task Planning: Application to Mobile Robotics", "creators": [ { "creatorType": "author", "firstName": "C.", "lastName": "Galindo" }, { "creatorType": "author", "firstName": "J. -A", "lastName": "Fernandez-Madrigal" }, { "creatorType": "author", "firstName": "J.", "lastName": "Gonzalez" } ], "abstractNote": "To date, no solution has been proposed to human-machine interactive task planning that deals simultaneously with two important issues: 1) the capability of processing large amounts of information in planning (as it is needed in any real application) and 2) being efficient in human-machine communication (a proper set of symbols for human-machine interaction may not be suitable for efficient automatic planning and vice versa). In this paper, we formalize a symbolic model of the environment to solve these issues in a natural form through a human-inspired mechanism that structures knowledge in multiple hierarchies. Planning with a hierarchical model may be efficient even in cases where the lack of hierarchical information would make it intractable. However, in addition, our multihierarchical model is able to use the symbols that are most familiar to each human user for interaction, thus achieving efficiency in human-machine communication without compromising the task-planning performance. We formalize here a general interactive task-planning process which is then particularized to be applied to a mobile robotic application. The suitability of our approach has been demonstrated with examples and experiments.", "publicationTitle": "IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics", "publisher": "", "place": "", "date": "June 2008", "volume": "38", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "785-798", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1109/TSMCB.2008.920227", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "1083-4419", "archive": "", "archiveLocation": "", "shortTitle": "Multihierarchical Interactive Task Planning", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Artificial intelligence", "type": 1 }, { "tag": "Computer Simulation", "type": 1 }, { "tag": "Decision Making", "type": 1 }, { "tag": "Decision Support Techniques", "type": 1 }, { "tag": "Models, Theoretical", "type": 1 }, { "tag": "Motion", "type": 1 }, { "tag": "hierarchical task planning", "type": 1 }, { "tag": "human-inspired mechanism", "type": 1 }, { "tag": "human-machine interaction", "type": 1 }, { "tag": "interactive systems", "type": 1 }, { "tag": "interactive task planning", "type": 1 }, { "tag": "mobile robotics", "type": 1 }, { "tag": "mobile robots", "type": 1 }, { "tag": "multi hierarchical interactive task planning", "type": 1 }, { "tag": "robotics", "type": 1 }, { "tag": "world modeling", "type": 1 } ], "collections": [ "FJFG6VFC" ], "relations": {}, "dateAdded": "2012-09-26T11:00:42Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "7XBDJZH8", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/7XBDJZH8", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/7XBDJZH8", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Gu and Hu", "parsedDate": "2004-05-26", "numChildren": 0 }, "data": { "key": "7XBDJZH8", "version": 1, "itemType": "conferencePaper", "title": "Teaching robots to coordinate its behaviours", "creators": [ { "creatorType": "author", "firstName": "D.", "lastName": "Gu" }, { "creatorType": "author", "firstName": "H.", "lastName": "Hu" } ], "abstractNote": "Behaviour co-ordination is one of the major problems in behaviour-based robotics. This paper presents a teaching method for mobile robots to learn behaviour coordination. In this method, the sensory information is abstracted into a limited number of feature states that correspond to physical events in the interactive process between a robot and its environment. The continuous motor actions are abstracted into a limited number of behaviours. The goal of the behaviour co-ordination is to map the feature states into the behaviours in the light of environment rewards. The teaching process consists of an imitation stage and an autonomous learning stage. Both stages employ Q-learning algorithms to implement the mapping. The imitation stage serves as a preliminary stage for the teaching method. The learning result is used to bootstrap the autonomous learning stage. Experiments are conducted in the domain of soccer playing by Sony legged robots. Experiment results show that the robots can acquire behaviour coordination ability.", "proceedingsTitle": "2004 IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04", "conferenceName": "2004 IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04", "publisher": "IEEE", "place": "", "date": "April 26-May 1, 2004", "eventPlace": "", "volume": "4", "issue": "", "numberOfVolumes": "", "pages": "3721- 3726 Vol.4", "series": "", "seriesNumber": "", "DOI": "10.1109/ROBOT.2004.1308842", "ISBN": "0-7803-8232-3", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Computer science", "type": 1 }, { "tag": "Education", "type": 1 }, { "tag": "Educational robots", "type": 1 }, { "tag": "Humans", "type": 1 }, { "tag": "Leaching", "type": 1 }, { "tag": "Learning systems", "type": 1 }, { "tag": "Legged locomotion", "type": 1 }, { "tag": "Q-learning algorithms", "type": 1 }, { "tag": "Robot kinematics", "type": 1 }, { "tag": "Robot sensing systems", "type": 1 }, { "tag": "Sony legged robots", "type": 1 }, { "tag": "autonomous learning stage", "type": 1 }, { "tag": "behaviour based robotics", "type": 1 }, { "tag": "behaviour coordination", "type": 1 }, { "tag": "continuous motor actions", "type": 1 }, { "tag": "environment rewards", "type": 1 }, { "tag": "feature states", "type": 1 }, { "tag": "interactive process", "type": 1 }, { "tag": "learning (artificial intelligence)", "type": 1 }, { "tag": "mobile robots", "type": 1 }, { "tag": "robot programming", "type": 1 }, { "tag": "sensory information", "type": 1 }, { "tag": "teaching method", "type": 1 }, { "tag": "teaching process", "type": 1 } ], "collections": [ "G6NQMPUV" ], "relations": {}, "dateAdded": "2012-09-26T11:00:42Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "5IANPNTM", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/5IANPNTM", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/5IANPNTM", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Matsikis et al.", "parsedDate": "2003-10-27", "numChildren": 0 }, "data": { "key": "5IANPNTM", "version": 1, "itemType": "conferencePaper", "title": "A behaviour coordination manager for a mobile manipulator", "creators": [ { "creatorType": "author", "firstName": "A.", "lastName": "Matsikis" }, { "creatorType": "author", "firstName": "F.", "lastName": "Schulte" }, { "creatorType": "author", "firstName": "F.", "lastName": "Broicher" }, { "creatorType": "author", "firstName": "K. -F", "lastName": "Kraiss" } ], "abstractNote": "In this paper a behaviour coordination manager for a mobile manipulator is proposed. The manager activates and coordinates purposive perception-action units, so-called behaviours, of a mobile manipulator based on a task provided by a deliberative planning system. As a decision making mechanism for the behaviour coordination Bayesian belief networks are applied. The Bayesian belief networks are trained to learn the influence of the behaviours on the manipulators movement in each situation. After development, training, and testing in a virtual environment, the implemented module is transferred to a real mobile manipulator and evaluated there. Finally, experimental results are presented.", "proceedingsTitle": "2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2003. (IROS 2003). Proceedings", "conferenceName": "2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2003. (IROS 2003). Proceedings", "publisher": "IEEE", "place": "", "date": "27-31 Oct. 2003", "eventPlace": "", "volume": "1", "issue": "", "numberOfVolumes": "", "pages": "174- 181 vol.1", "series": "", "seriesNumber": "", "DOI": "10.1109/IROS.2003.1250624", "ISBN": "0-7803-7860-1", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Bayesian belief networks", "type": 1 }, { "tag": "Bayesian methods", "type": 1 }, { "tag": "Computer science", "type": 1 }, { "tag": "Decision Making", "type": 1 }, { "tag": "Management training", "type": 1 }, { "tag": "Mobile computing", "type": 1 }, { "tag": "Robot kinematics", "type": 1 }, { "tag": "Sensor phenomena and characterization", "type": 1 }, { "tag": "Service robots", "type": 1 }, { "tag": "Testing", "type": 1 }, { "tag": "behaviour coordination manager", "type": 1 }, { "tag": "belief networks", "type": 1 }, { "tag": "decision making mechanism", "type": 1 }, { "tag": "deliberative planning system", "type": 1 }, { "tag": "learning (artificial intelligence)", "type": 1 }, { "tag": "manipulators", "type": 1 }, { "tag": "mobile manipulator", "type": 1 }, { "tag": "mobile robots", "type": 1 }, { "tag": "perception-action units", "type": 1 }, { "tag": "virtual environment", "type": 1 } ], "collections": [ "G6NQMPUV" ], "relations": {}, "dateAdded": "2012-09-26T11:00:42Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "M83D8VRV", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/M83D8VRV", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/M83D8VRV", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Edsinger and Kemp", "parsedDate": "2006-12-04", "numChildren": 0 }, "data": { "key": "M83D8VRV", "version": 1, "itemType": "conferencePaper", "title": "Manipulation in Human Environments", "creators": [ { "creatorType": "author", "firstName": "A.", "lastName": "Edsinger" }, { "creatorType": "author", "firstName": "C. C", "lastName": "Kemp" } ], "abstractNote": "Robots that work alongside us in our homes and workplaces could extend the time an elderly person can live at home, provide physical assistance to a worker on an assembly line, or help with household chores. In order to assist us in these ways, robots will need to successfully perform manipulation tasks within human environments. Human environments present special challenges for robot manipulation since they are complex, dynamic, uncontrolled, and difficult to perceive reliably. In this paper we present a behavior-based control system that enables a humanoid robot, Domo, to help a person place objects on a shelf. Domo is able to physically locate the shelf, socially cue a person to hand it an object, grasp the object that has been handed to it, transfer the object to the hand that is closest to the shelf, and place the object on the shelf. We use this behavior-based control system to illustrate three themes that characterize our approach to manipulation in human environments. The first theme, cooperative manipulation, refers to the advantages that can be gained by having the robot work with a person to cooperatively perform manipulation tasks. The second theme, task relevant features, emphasizes the benefits of carefully selecting the aspects of the world that are to be perceived and acted upon during a manipulation task. The third theme, let the body do the thinking, encompasses several ways in which a robot can use its body to simplify manipulation tasks.", "proceedingsTitle": "2006 6th IEEE-RAS International Conference on Humanoid Robots", "conferenceName": "2006 6th IEEE-RAS International Conference on Humanoid Robots", "publisher": "IEEE", "place": "", "date": "4-6 Dec. 2006", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "102-109", "series": "", "seriesNumber": "", "DOI": "10.1109/ICHR.2006.321370", "ISBN": "1-4244-0200-X", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Books", "type": 1 }, { "tag": "Computer science", "type": 1 }, { "tag": "Control systems", "type": 1 }, { "tag": "Domo humanoid robot", "type": 1 }, { "tag": "Employment", "type": 1 }, { "tag": "Humanoid robots", "type": 1 }, { "tag": "Humans", "type": 1 }, { "tag": "Manipulator dynamics", "type": 1 }, { "tag": "Path planning", "type": 1 }, { "tag": "Robotic assembly", "type": 1 }, { "tag": "Senior citizens", "type": 1 }, { "tag": "behavior-based control system", "type": 1 }, { "tag": "cooperative manipulation", "type": 1 }, { "tag": "human environment", "type": 1 }, { "tag": "man-machine systems", "type": 1 }, { "tag": "manipulators", "type": 1 }, { "tag": "mobile robots", "type": 1 }, { "tag": "object grasping", "type": 1 }, { "tag": "person-robot cooperation", "type": 1 }, { "tag": "robot manipulation", "type": 1 }, { "tag": "task relevant features", "type": 1 } ], "collections": [ "G6NQMPUV" ], "relations": {}, "dateAdded": "2012-09-26T11:00:42Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "2ITDTRIT", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/2ITDTRIT", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/2ITDTRIT", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Hoff and Bekey", "parsedDate": "1995-12", "numChildren": 0 }, "data": { "key": "2ITDTRIT", "version": 1, "itemType": "conferencePaper", "title": "An architecture for behaviour coordination learning", "creators": [ { "creatorType": "author", "firstName": "J.", "lastName": "Hoff" }, { "creatorType": "author", "firstName": "G.", "lastName": "Bekey" } ], "abstractNote": "This paper describes a neural architecture for learning coordination of different behaviours in a situated agent. Behaviour-oriented approaches define the control of an agent directly in terms of its tasks. A key challenge is how to manage the agent's ongoing tasks so that action conflict is minimized and the desired levels of compliance with overall goals are achieved. We present mechanisms for adapting the coordination strategy through short- and long-term adaptive inhibition and time-varying performance feedback. Finally, we present preliminary experimental results for a simulated robot which demonstrate the effectiveness of this method", "proceedingsTitle": ", IEEE International Conference on Neural Networks, 1995. Proceedings", "conferenceName": ", IEEE International Conference on Neural Networks, 1995. Proceedings", "publisher": "IEEE", "place": "", "date": "Nov/Dec 1995", "eventPlace": "", "volume": "5", "issue": "", "numberOfVolumes": "", "pages": "2375-2380 vol.5", "series": "", "seriesNumber": "", "DOI": "10.1109/ICNN.1995.487733", "ISBN": "0-7803-2768-3", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Computer architecture", "type": 1 }, { "tag": "Computer science", "type": 1 }, { "tag": "Intelligent agent", "type": 1 }, { "tag": "Intelligent robots", "type": 1 }, { "tag": "Neural engineering", "type": 1 }, { "tag": "Path planning", "type": 1 }, { "tag": "Robot kinematics", "type": 1 }, { "tag": "Robustness", "type": 1 }, { "tag": "Statistical analysis", "type": 1 }, { "tag": "Voting", "type": 1 }, { "tag": "adaptive inhibition", "type": 1 }, { "tag": "adaptive systems", "type": 1 }, { "tag": "behaviour coordination learning", "type": 1 }, { "tag": "compliance control", "type": 1 }, { "tag": "cooperative systems", "type": 1 }, { "tag": "decentralised architecture", "type": 1 }, { "tag": "intelligent agents", "type": 1 }, { "tag": "intelligent control", "type": 1 }, { "tag": "learning (artificial intelligence)", "type": 1 }, { "tag": "mobile robots", "type": 1 }, { "tag": "navigation", "type": 1 }, { "tag": "neural architecture", "type": 1 }, { "tag": "neural nets", "type": 1 }, { "tag": "neurocontrollers", "type": 1 }, { "tag": "performance feedback", "type": 1 } ], "collections": [ "G6NQMPUV" ], "relations": {}, "dateAdded": "2012-09-26T11:00:42Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "X9T45MKM", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/X9T45MKM", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/X9T45MKM", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Costelha and Lima", "parsedDate": "2007-11-29", "numChildren": 0 }, "data": { "key": "X9T45MKM", "version": 1, "itemType": "conferencePaper", "title": "Modelling, analysis and execution of robotic tasks using petri nets", "creators": [ { "creatorType": "author", "firstName": "H.", "lastName": "Costelha" }, { "creatorType": "author", "firstName": "P.", "lastName": "Lima" } ], "abstractNote": "This paper introduces Petri net based models of robotic tasks, which can be used to analyse and synthesise task plans, taking into account a Petri net model that abstracts the relevant features from the robot environment as well. Logical analysis concerning deadlocks and resource conservation can be performed over the ordinary version of the model. A task plan modeled by a Petri net can be extracted from the generalised stochastic version of the model, representing the optimal plan given a probabilistic measure of uncertainty associated to the effects of its composing actions. The Petri net representing the model is suitable for being ran directly within the code, as well as for plan monitoring during execution time. Simulation results illustrating the methodology are presented for a robotic soccer scenario.", "proceedingsTitle": "IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007. IROS 2007", "conferenceName": "IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007. IROS 2007", "publisher": "IEEE", "place": "", "date": "Oct. 29 2007-Nov. 2 2007", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "1449-1454", "series": "", "seriesNumber": "", "DOI": "10.1109/IROS.2007.4399365", "ISBN": "978-1-4244-0912-9", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Control system synthesis", "type": 1 }, { "tag": "Discrete event systems", "type": 1 }, { "tag": "Intelligent robots", "type": 1 }, { "tag": "Monitoring", "type": 1 }, { "tag": "Notice of Violation", "type": 1 }, { "tag": "Performance analysis", "type": 1 }, { "tag": "Petri net model", "type": 1 }, { "tag": "Petri nets", "type": 1 }, { "tag": "Power system modeling", "type": 1 }, { "tag": "State-space methods", "type": 1 }, { "tag": "Stochastic processes", "type": 1 }, { "tag": "USA Councils", "type": 1 }, { "tag": "control system analysis", "type": 1 }, { "tag": "generalised stochastic version", "type": 1 }, { "tag": "logical analysis", "type": 1 }, { "tag": "mobile robots", "type": 1 }, { "tag": "multi-robot systems", "type": 1 }, { "tag": "probabilistic measure", "type": 1 }, { "tag": "probability", "type": 1 }, { "tag": "resource conservation", "type": 1 }, { "tag": "robotic soccer", "type": 1 }, { "tag": "robotic tasks", "type": 1 }, { "tag": "sport", "type": 1 }, { "tag": "task analysis", "type": 1 }, { "tag": "task plan modeling", "type": 1 } ], "collections": [ "BMC9XP8I" ], "relations": {}, "dateAdded": "2012-09-26T11:00:35Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "PKTT5DTJ", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/PKTT5DTJ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/PKTT5DTJ", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Milighetti and Kuntze", "parsedDate": "2007-11-29", "numChildren": 0 }, "data": { "key": "PKTT5DTJ", "version": 1, "itemType": "conferencePaper", "title": "Fuzzy based decision making for the discrete-continuous control of humanoid robots", "creators": [ { "creatorType": "author", "firstName": "G.", "lastName": "Milighetti" }, { "creatorType": "author", "firstName": "H. -B", "lastName": "Kuntze" } ], "abstractNote": "Within the next years a new generation of humanoid robots able to manage autonomously sophisticated tasks in a complex, time varying domestic and public environment is going to be developed. To cope with these advanced requirements a new multi-sensor based discrete- continuous supervisory control concept is proposed, which is able to accomplish even complex human skills. Each skill is divided into a sequence of elementary actions (so called Primitive Skills). Depending on the multi-sensor perception of the current state of the system, the discrete control has to provide an optimal selection and activation of the appropriate sequence of action and control strategy. An on-line decision making algorithm based on the structure of Primitive Skills (PS) has been implemented. On a lower level the continuous control has to assure that each PS is performed by means of the most appropriate sub-controllers. The theoretical approach and first experimental results of the ongoing research are presented in this paper.", "proceedingsTitle": "IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007. IROS 2007", "conferenceName": "IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007. IROS 2007", "publisher": "IEEE", "place": "", "date": "Oct. 29 2007-Nov. 2 2007", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "3580-3585", "series": "", "seriesNumber": "", "DOI": "10.1109/IROS.2007.4399054", "ISBN": "978-1-4244-0912-9", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Control systems", "type": 1 }, { "tag": "Decision Making", "type": 1 }, { "tag": "Fuzzy control", "type": 1 }, { "tag": "Humanoid robots", "type": 1 }, { "tag": "Humans", "type": 1 }, { "tag": "Intelligent robots", "type": 1 }, { "tag": "Optimal control", "type": 1 }, { "tag": "Petri-nets", "type": 1 }, { "tag": "Robot control", "type": 1 }, { "tag": "Robot sensing systems", "type": 1 }, { "tag": "Service robots", "type": 1 }, { "tag": "continuous systems", "type": 1 }, { "tag": "discrete systems", "type": 1 }, { "tag": "discrete-continuous control", "type": 1 }, { "tag": "discrete-continuous supervisory control", "type": 1 }, { "tag": "fuzzy based decision making", "type": 1 }, { "tag": "fuzzy decision making", "type": 1 }, { "tag": "fuzzy set theory", "type": 1 }, { "tag": "humanoid robot", "type": 1 }, { "tag": "multisensor", "type": 1 }, { "tag": "online decision making algorithm", "type": 1 }, { "tag": "primitive Skill", "type": 1 }, { "tag": "sensor fusion", "type": 1 } ], "collections": [ "NSA4T8A6" ], "relations": {}, "dateAdded": "2012-09-26T11:00:42Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "KFZZGN7U", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/KFZZGN7U", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/KFZZGN7U", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Milighetti and Kuntze", "parsedDate": "2006-10-09", "numChildren": 0 }, "data": { "key": "KFZZGN7U", "version": 1, "itemType": "conferencePaper", "title": "On the Discrete-Continuous Control of Basic Skills for Humanoid Robots", "creators": [ { "creatorType": "author", "firstName": "G.", "lastName": "Milighetti" }, { "creatorType": "author", "firstName": "H. B", "lastName": "Kuntze" } ], "abstractNote": "Within the next years a new generation of humanoid robots is going to be developed being able to manage autonomously sophisticated tasks in a complex, time variant domestic environment. To cope with these advanced requirements a new multi-sensor based discrete-continuous supervisory control concept is proposed, which is able to accomplish even complex human skills. Each skill is divided into a sequence of primitive skills (PS). Depending on the multisensor perception of the robot state, the discrete control has to provide an optimal selection and activation of different PS. On the other hand the continuous control has to assure that each PS is performed by means of the most appropriate sub-controllers. Both theoretical approach and experimental results of the ongoing research are presented in this paper", "proceedingsTitle": "2006 IEEE/RSJ International Conference on Intelligent Robots and Systems", "conferenceName": "2006 IEEE/RSJ International Conference on Intelligent Robots and Systems", "publisher": "IEEE", "place": "", "date": "9-15 Oct. 2006", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "3474-3479", "series": "", "seriesNumber": "", "DOI": "10.1109/IROS.2006.282589", "ISBN": "1-4244-0258-1", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Control systems", "type": 1 }, { "tag": "Environmental management", "type": 1 }, { "tag": "Human robot interaction", "type": 1 }, { "tag": "Humanoid robots", "type": 1 }, { "tag": "Optimal control", "type": 1 }, { "tag": "Robot control", "type": 1 }, { "tag": "Robot sensing systems", "type": 1 }, { "tag": "Robotic assembly", "type": 1 }, { "tag": "Service robots", "type": 1 }, { "tag": "Supervisory control", "type": 1 }, { "tag": "discrete systems", "type": 1 }, { "tag": "discrete-continuous control", "type": 1 }, { "tag": "discrete-continuous supervisory control concept", "type": 1 }, { "tag": "humanoid robot", "type": 1 }, { "tag": "mobile robots", "type": 1 }, { "tag": "multisensor", "type": 1 }, { "tag": "multisensor perception", "type": 1 }, { "tag": "primitive Skill", "type": 1 }, { "tag": "primitive skills", "type": 1 }, { "tag": "telerobotics", "type": 1 } ], "collections": [ "NSA4T8A6" ], "relations": {}, "dateAdded": "2012-09-26T11:00:42Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "X2FHE7PI", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/X2FHE7PI", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/X2FHE7PI", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Milighetti et al.", "parsedDate": "2005-07-18", "numChildren": 0 }, "data": { "key": "X2FHE7PI", "version": 1, "itemType": "conferencePaper", "title": "On a primitive skill-based supervisory robot control architecture", "creators": [ { "creatorType": "author", "firstName": "G.", "lastName": "Milighetti" }, { "creatorType": "author", "firstName": "H. B", "lastName": "Kuntze" }, { "creatorType": "author", "firstName": "C. W", "lastName": "Frey" }, { "creatorType": "author", "firstName": "B.", "lastName": "Diestel-Feddersen" }, { "creatorType": "author", "firstName": "J.", "lastName": "Balzer" } ], "abstractNote": "Smart interaction of humanoid robots in a complex public, private or industrial environment requires the introduction of primitive skill-based discrete-continuous supervisory control concepts. The functionality of the proposed hierarchical robot supervisory control architecture captures both the hierarchy that is required for representing complex skills as well as the mechanisms for detecting failures during their execution. At first by means of several complementary (e.g. internal, optical, tactile or acoustic) sensors and by neuro-fuzzy based fusion of relevant sensor features, the actual motion phase or fault event is continuously diagnosed. Depending on the identified motion phase or random fault event, the most appropriate discrete-continuous control strategy coping optimally with the corresponding situation will be selected and executed. First experimental and simulation results are reported in this paper", "proceedingsTitle": ", 12th International Conference on Advanced Robotics, 2005. ICAR '05. Proceedings", "conferenceName": ", 12th International Conference on Advanced Robotics, 2005. ICAR '05. Proceedings", "publisher": "IEEE", "place": "", "date": "18-20 July 2005", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "141-147", "series": "", "seriesNumber": "", "DOI": "10.1109/ICAR.2005.1507404", "ISBN": "0-7803-9178-0", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Acoustic sensors", "type": 1 }, { "tag": "Humanoid robots", "type": 1 }, { "tag": "Industrial control", "type": 1 }, { "tag": "Optical sensors", "type": 1 }, { "tag": "Robot control", "type": 1 }, { "tag": "SCADA systems", "type": 1 }, { "tag": "Sensor phenomena and characterization", "type": 1 }, { "tag": "Service robots", "type": 1 }, { "tag": "Supervisory control", "type": 1 }, { "tag": "Tactile sensors", "type": 1 }, { "tag": "discrete systems", "type": 1 }, { "tag": "discrete-continuous control", "type": 1 }, { "tag": "fuzzy neural nets", "type": 1 }, { "tag": "hierarchical robot supervisory control", "type": 1 }, { "tag": "hierarchical supervisory control architecture", "type": 1 }, { "tag": "multisensor perception", "type": 1 }, { "tag": "neurofuzzy based fusion", "type": 1 }, { "tag": "neurofuzzy diagnosis", "type": 1 }, { "tag": "primitive skills", "type": 1 }, { "tag": "sensor fusion", "type": 1 }, { "tag": "supervisory robot control architecture", "type": 1 } ], "collections": [ "NSA4T8A6" ], "relations": {}, "dateAdded": "2012-09-26T11:00:42Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "S9DK2PVV", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/S9DK2PVV", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/S9DK2PVV", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Galindo et al.", "parsedDate": "2008-11-30", "numChildren": 0 }, "data": { "key": "S9DK2PVV", "version": 1, "itemType": "journalArticle", "title": "Robot task planning using semantic maps", "creators": [ { "creatorType": "author", "firstName": "Cipriano", "lastName": "Galindo" }, { "creatorType": "author", "firstName": "Juan-Antonio", "lastName": "Fernández-Madrigal" }, { "creatorType": "author", "firstName": "Javier", "lastName": "González" }, { "creatorType": "author", "firstName": "Alessandro", "lastName": "Saffiotti" } ], "abstractNote": "Task planning for mobile robots usually relies solely on spatial information and on shallow domain knowledge, such as labels attached to objects and places. Although spatial information is necessary for performing basic robot operations (navigation and localization), the use of deeper domain knowledge is pivotal to endow a robot with higher degrees of autonomy and intelligence. In this paper, we focus on semantic knowledge, and show how this type of knowledge can be profitably used for robot task planning. We start by defining a specific type of semantic maps, which integrates hierarchical spatial information and semantic knowledge. We then proceed to describe how these semantic maps can improve task planning in two ways: extending the capabilities of the planner by reasoning about semantic information, and improving the planning efficiency in large domains. We show several experiments that demonstrate the effectiveness of our solutions in a domain involving robot navigation in a domestic environment.", "publicationTitle": "Robotics and Autonomous Systems", "publisher": "", "place": "", "date": "November 30, 2008", "volume": "56", "issue": "11", "section": "", "partNumber": "", "partTitle": "", "pages": "955-966", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.robot.2008.08.007", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0921889008001188", "accessDate": "2011-09-29T13:23:49Z", "PMID": "", "PMCID": "", "ISSN": "0921-8890", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Cognitive robotics", "type": 1 }, { "tag": "Knowledge representation", "type": 1 }, { "tag": "Robot maps", "type": 1 }, { "tag": "mobile robotics", "type": 1 }, { "tag": "task planning", "type": 1 } ], "collections": [ "FJFG6VFC" ], "relations": {}, "dateAdded": "2012-09-26T11:00:42Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "PXZKFP4I", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/PXZKFP4I", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/PXZKFP4I", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Galindo et al.", "parsedDate": "2004-08", "numChildren": 0 }, "data": { "key": "PXZKFP4I", "version": 1, "itemType": "journalArticle", "title": "Improving efficiency in mobile robot task planning through world abstraction", "creators": [ { "creatorType": "author", "firstName": "C.", "lastName": "Galindo" }, { "creatorType": "author", "firstName": "J. -A", "lastName": "Fernandez-Madrigal" }, { "creatorType": "author", "firstName": "J.", "lastName": "Gonzalez" } ], "abstractNote": "Task planning in mobile robotics should be performed efficiently, due to real-time requirements of robot-environment interaction. Its computational efficiency depends both on the number of operators (actions the robot can perform without planning) and the size of the world states (descriptions of the world before and after the application of operators). Thus, in real robotic applications, where both components can be large, planning may turn inefficient, and even unsolvable. In the artificial intelligence (AI) literature on planning, little attention has been put into efficient management of large-scale world descriptions. In real large-scale situations, conventional AI planners (in spite of the most modern improvements) may consume intractable amounts of storage and computing time, due to the huge amount of information. This paper proposes a new approach to task planning called \"hierarchical task planning through world abstraction\" that, by hierarchically arranging the world representation, becomes a good complement of Stanford Research Institute Problem Solver-style planners, significantly improving their computational efficiency. Broadly speaking, our approach works by first solving the task-planning problem in a highly abstracted model of the environment of the robot, and then refines the solution under more detailed models, where irrelevant world elements can be ignored, due to the results previously obtained at abstracted levels. Among the different implementations that can be made with our general strategy, we describe two that use a graph-based hierarchical world representation named the \"annotated and hierarchical\" graph. We show experiments, as well as results of a mobile robot operating in a large-scale environment, that demonstrate an important improvement in the efficiency of our algorithms with respect to conventional (both hierarchical and nonhierarchical) planning and their nice integration with existing planners.", "publicationTitle": "IEEE Transactions on Robotics", "publisher": "", "place": "", "date": "Aug. 2004", "volume": "20", "issue": "4", "section": "", "partNumber": "", "partTitle": "", "pages": "677- 690", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1109/TRO.2004.829480", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "1552-3098", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Artificial intelligence", "type": 1 }, { "tag": "Intelligent robots", "type": 1 }, { "tag": "Large-scale systems", "type": 1 }, { "tag": "Motion planning", "type": 1 }, { "tag": "Orbital robotics", "type": 1 }, { "tag": "Path planning", "type": 1 }, { "tag": "Production planning", "type": 1 }, { "tag": "Robot sensing systems", "type": 1 }, { "tag": "Robotic assembly", "type": 1 }, { "tag": "annotated graph", "type": 1 }, { "tag": "computational efficiency", "type": 1 }, { "tag": "graph theory", "type": 1 }, { "tag": "hierarchical graph", "type": 1 }, { "tag": "hierarchical task planning", "type": 1 }, { "tag": "large-scale environment", "type": 1 }, { "tag": "mobile robotics", "type": 1 }, { "tag": "mobile robots", "type": 1 }, { "tag": "planning (artificial intelligence)", "type": 1 }, { "tag": "robot-environment interaction", "type": 1 }, { "tag": "robotics", "type": 1 }, { "tag": "world abstraction", "type": 1 }, { "tag": "world modeling", "type": 1 } ], "collections": [ "FJFG6VFC" ], "relations": {}, "dateAdded": "2012-09-26T11:00:42Z", "dateModified": "2012-09-26T11:01:40Z" } }, { "key": "3UNDNKJT", "version": 1, "library": { "type": "group", "id": 91105, "name": "PlanningExecutionSimulation", "links": { "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/91105/items/3UNDNKJT", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/planningexecutionsimulation/items/3UNDNKJT", "type": "text/html" } }, "meta": { "createdByUser": { "id": 739318, "username": "rjmjanssen", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/rjmjanssen", "type": "text/html" } } }, "creatorSummary": "Minkyoung Kim and Hyun Kim", "parsedDate": "2006-07-10", "numChildren": 0 }, "data": { "key": "3UNDNKJT", "version": 1, "itemType": "conferencePaper", "title": "Behavior Coordination Mechanism for Intelligent Home", "creators": [ { "creatorType": "author", "firstName": "", "lastName": "Minkyoung Kim" }, { "creatorType": "author", "firstName": "", "lastName": "Hyun Kim" } ], "abstractNote": "Ubiquitous computing technology has brought high availabilities of network environments. At the same time, it has become a prerequisite for providing appropriate services in accordance with user contexts. For the context-aware services, there have been a wide variety of task applications, but coordination among tasks is still a major issue. Here, this paper proposes behavior coordination mechanism using action selection mechanism for intelligent home environments. In behavior-based control of a robot, a behavior is a series of actions towards a system objective. In the same way, high level applications for a smart home can be considered behaviors of a robot since task applications generally have activity scenarios to achieve their own objectives; a robot is not just a physical single robot but a robotic system from a broad point of view. In order to avoid multiple objective behavior conflict, this paper focuses on the subsumption architecture as an action section mechanism, and also introduces service management techniques for seamless services at an intelligent home", "proceedingsTitle": "5th IEEE/ACIS International Conference on Computer and Information Science, 2006 and 2006 1st IEEE/ACIS International Workshop on Component-Based Software Engineering, Software Architecture and Reuse. ICIS-COMSAR 2006", "conferenceName": "5th IEEE/ACIS International Conference on Computer and Information Science, 2006 and 2006 1st IEEE/ACIS International Workshop on Component-Based Software Engineering, Software Architecture and Reuse. ICIS-COMSAR 2006", "publisher": "IEEE", "place": "", "date": "10-12 July 2006", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "452-457", "series": "", "seriesNumber": "", "DOI": "10.1109/ICIS-COMSAR.2006.25", "ISBN": "0-7695-2613-6", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Ambient intelligence", "type": 1 }, { "tag": "Computer architecture", "type": 1 }, { "tag": "Context-aware services", "type": 1 }, { "tag": "Control systems", "type": 1 }, { "tag": "Fuzzy systems", "type": 1 }, { "tag": "Home computing", "type": 1 }, { "tag": "Intelligent robots", "type": 1 }, { "tag": "Learning systems", "type": 1 }, { "tag": "Robot kinematics", "type": 1 }, { "tag": "Ubiquitous computing", "type": 1 }, { "tag": "action selection mechanism", "type": 1 }, { "tag": "activity scenarios", "type": 1 }, { "tag": "behavior coordination mechanism", "type": 1 }, { "tag": "behavior-based control", "type": 1 }, { "tag": "home automation", "type": 1 }, { "tag": "intelligent home environments", "type": 1 }, { "tag": "learning (artificial intelligence)", "type": 1 }, { "tag": "multiple objective behavior conflict", "type": 1 }, { "tag": "network environments", "type": 1 }, { "tag": "robotic system", "type": 1 }, { "tag": "service management techniques", "type": 1 }, { "tag": "subsumption architecture", "type": 1 }, { "tag": "task coordination", "type": 1 }, { "tag": "ubiquitous computing technology", "type": 1 } ], "collections": [ "G6NQMPUV" ], "relations": {}, "dateAdded": "2012-09-26T11:00:42Z", "dateModified": "2012-09-26T11:01:40Z" } } ]