{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/90674"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/90674","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Cooperative collision avoidance control and coordination for multiagent Lagrangian systems with disturbances","abstract":"Multi-agent systems like a network of autonomous robots, have tremendous potential in many military and civilian applications. But, even viewed as a pure academic problem, designing controllers for such complex systems is a matter of much interest. Controller design for multi-agent system might focus on achieving several objectives, such as formation control, coverage control, consensus, target capture, pursuit evasion etc., while all at the same time aiming to be optimal in some sense, or following certain constraints imposed by the environment or communication limitations. Whatever is the objective, we always want to have a safety guarantee for the agents; the agents should avoid collisions with themselves and any static obstacles, while performing an objective. This thesis studies one such controller, which guarantees collision avoidance among the agents, in presence of bounded disturbances, while the agents carry out a coordination objective. The agents are assumed to follow a Lagrangian dynamics. The collision avoidance controller takes up the second part of the thesis. In the first part of this thesis, a particular Lagrangian system, the Raven II surgical robot, is studied in with the aim of highlighting the process of modelling and identifying such system. This is done for two reasons. One because Lagrangian dynamics is commonly used to model the agents in a multi-agent system. And second reason that motivates the modelling Raven II in part I, is to aid in future research direction pertaining to the control of Raven II.","abstract_html":"Multi-agent systems like a network of autonomous robots, have tremendous potential in many military and civilian applications. But, even viewed as a pure academic problem, designing controllers for such complex systems is a matter of much interest. Controller design for multi-agent system might focus on achieving several objectives, such as formation control, coverage control, consensus, target capture, pursuit evasion etc., while all at the same time aiming to be optimal in some sense, or following certain constraints imposed by the environment or communication limitations. Whatever is the objective, we always want to have a safety guarantee for the agents; the agents should avoid collisions with themselves and any static obstacles, while performing an objective. This thesis studies one such controller, which guarantees collision avoidance among the agents, in presence of bounded disturbances, while the agents carry out a coordination objective. The agents are assumed to follow a Lagrangian dynamics. The collision avoidance controller takes up the second part of the thesis. In the first part of this thesis, a particular Lagrangian system, the Raven II surgical robot, is studied in with the aim of highlighting the process of modelling and identifying such system. This is done for two reasons. One because Lagrangian dynamics is commonly used to model the agents in a multi-agent system. And second reason that motivates the modelling Raven II in part I, is to aid in future research direction pertaining to the control of Raven II.","abstract_has_math":false,"creators":["Deka, Shankar Anand"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Mechanical Engineering","degree_department":null,"school":null,"contributors":["Stipanović, Dušan M."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-07-07T19:58:15Z","date_published":"2016-07-07T19:58:15Z","updated_at":"2026-07-22T22:26:34Z","subjects":["Mutliagent systems","Collision avoidance","Coordination"],"languages":["en"],"rights":["Copyright 2016 Shankar Anand Deka"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/90674","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Stipanović, Dušan M."]},{"key":"dc:creator","label":"Author","values":["Deka, Shankar Anand"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2016-07-07T19:58:15Z","2016-04-28","2016-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Mutliagent systems","Collision avoidance","Coordination"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2016 Shankar Anand Deka"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/90674"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Multi-agent systems like a network of autonomous robots, have tremendous potential in many military and civilian applications. But, even viewed as a pure academic problem, designing controllers for such complex systems is a matter of much interest. Controller design for multi-agent system might focus on achieving several objectives, such as formation control, coverage control, consensus, target capture, pursuit evasion etc., while all at the same time aiming to be optimal in some sense, or following certain constraints imposed by the environment or communication limitations. Whatever is the objective, we always want to have a safety guarantee for the agents; the agents should avoid collisions with themselves and any static obstacles, while performing an objective. This thesis studies one such controller, which guarantees collision avoidance among the agents, in presence of bounded disturbances, while the agents carry out a coordination objective. The agents are assumed to follow a Lagrangian dynamics. The collision avoidance controller takes up the second part of the thesis. In the first part of this thesis, a particular Lagrangian system, the Raven II surgical robot, is studied in with the aim of highlighting the process of modelling and identifying such system. This is done for two reasons. One because Lagrangian dynamics is commonly used to model the agents in a multi-agent system. And second reason that motivates the modelling Raven II in part I, is to aid in future research direction pertaining to the control of Raven II.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-07-07 without embargo terms","The student, Shankar Deka, accepted the attached license on 2016-04-26 at 23:06.","The student, Shankar Deka, submitted this Thesis for approval on 2016-04-26 at 23:13.","This Thesis was approved for publication on 2016-04-28 at 08:17.","DSpace SAF Submission Ingestion Package generated from Vireo submission #9537 on 2016-07-07 at 13:33:37","Made available in DSpace on 2016-07-07T19:58:15Z (GMT). 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Controller design for multi-agent system might focus on achieving several objectives, such as formation control, coverage control, consensus, target capture, pursuit evasion etc., while all at the same time aiming to be optimal in some sense, or following certain constraints imposed by the environment or communication limitations. Whatever is the objective, we always want to have a safety guarantee for the agents; the agents should avoid collisions with themselves and any static obstacles, while performing an objective. This thesis studies one such controller, which guarantees collision avoidance among the agents, in presence of bounded disturbances, while the agents carry out a coordination objective. The agents are assumed to follow a Lagrangian dynamics. The collision avoidance controller takes up the second part of the thesis. In the first part of this thesis, a particular Lagrangian system, the Raven II surgical robot, is studied in with the aim of highlighting the process of modelling and identifying such system. This is done for two reasons. One because Lagrangian dynamics is commonly used to model the agents in a multi-agent system. And second reason that motivates the modelling Raven II in part I, is to aid in future research direction pertaining to the control of Raven II.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-07-07 without embargo terms","The student, Shankar Deka, accepted the attached license on 2016-04-26 at 23:06.","The student, Shankar Deka, submitted this Thesis for approval on 2016-04-26 at 23:13.","This Thesis was approved for publication on 2016-04-28 at 08:17.","DSpace SAF Submission Ingestion Package generated from Vireo submission #9537 on 2016-07-07 at 13:33:37","Made available in DSpace on 2016-07-07T19:58:15Z (GMT). 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