Active risk management in dynamic teams of heterogeneous robots

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dc.contributor.authorChangizi, Soheil
dc.contributor.examiningcommitteeBunt, Andrea (Computer Science)
dc.contributor.examiningcommitteeMcNeill, Dean (Electrical and Computer Engineering)
dc.contributor.examiningcommitteeBaltes, Jacky (Computer Science)
dc.contributor.supervisorAnderson, John
dc.date.accessioned2024-09-03T20:35:32Z
dc.date.available2024-09-03T20:35:32Z
dc.date.issued2024-08-21
dc.date.submitted2024-08-21T21:37:42Zen_US
dc.degree.disciplineComputer Science
dc.degree.levelMaster of Science (M.Sc.)
dc.description.abstractIn Urban Search and Rescue (USAR), hazards such as structural collapse and fire can significantly endanger robots. To mitigate these risks, it is crucial to plan task allocations that adapt to dynamic environments. Most available strategies begin with evaluating the mission in advance and formulating a static plan, which may be inflexible for unforeseen changes. This project seeks to expand our lab’s existing framework by integrating Active Risk Management (ARM) into ongoing missions. The ARM module enhances adaptability by continuously monitoring environmental hazards and initiating risk mitigation tasks. Additionally, a novel method for detecting and escaping local minima allows robots to adjust their navigation patterns, preventing immobilization. The simulation environment now features realistic fire propagation, introducing a dynamic element that rigorously tests the effectiveness of the robots’ risk management strategies. By incorporating these advancements, we aim to increase mission success rates and significantly reduce robot damage in challenging USAR scenarios.
dc.description.noteOctober 2024
dc.identifier.urihttp://hdl.handle.net/1993/38497
dc.language.isoeng
dc.rightsopen accessen_US
dc.subjectUrban Search and Rescue
dc.subjectMulti-robot Teams
dc.titleActive risk management in dynamic teams of heterogeneous robots
dc.typemaster thesisen_US
local.subject.manitobano
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