Introduces probabilistically complete and asymptotically optimal sampling-based planners for multi-modal multi-robot multi-goal path planning by adapting standard methods to the composite space of all robots.
Cooperative task and motion planning for multi-arm assembly systems
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RAPIDDS unifies task-level and motion-level adaptation in human-robot teaming by modeling individualized spatial and temporal behaviors across multiple cycles and jointly optimizing schedules and diffusion-based motions.
citing papers explorer
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Sampling-Based Multi-Modal Multi-Robot Multi-Goal Path Planning
Introduces probabilistically complete and asymptotically optimal sampling-based planners for multi-modal multi-robot multi-goal path planning by adapting standard methods to the composite space of all robots.
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Multi-Cycle Spatio-Temporal Adaptation in Human-Robot Teaming
RAPIDDS unifies task-level and motion-level adaptation in human-robot teaming by modeling individualized spatial and temporal behaviors across multiple cycles and jointly optimizing schedules and diffusion-based motions.