首页|Investigators from University of Cambridge Release New Data on Robotics (Solving Simultaneous Target Assignment and Path Planning Efficiently With Time-independ ent Execution)
Investigators from University of Cambridge Release New Data on Robotics (Solving Simultaneous Target Assignment and Path Planning Efficiently With Time-independ ent Execution)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Current study results on Robotics have been publi shed. According to news reporting out ofCambridge, United Kingdom, by NewsRx ed itors, research stated, “Real-time planning for a combinedproblem of target ass ignment and path planning for multiple agents, also known as the unlabeled version of multi-agent path finding (MAPF), is crucial for high-level coordination in multi-agent systems, suchas pattern formation by robot swarms. This paper stud ies two aspects of unlabeled-MAPF: (1) offlinescenario: solving large instances using centralized approaches with a small computation time, and (2)online scen ario: executing unlabeled-MAPF, despite the timing uncertainties real robots fac e.”
CambridgeUnited KingdomEuropeEmerg ing TechnologiesMachine LearningRobotRoboticsUniversity of Cambridge
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