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Stop-N-Go: Search-based Conflict Resolution for Motion Planning of Multiple Robotic Manipulators
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Stop-N-Go: Search-based Conflict Resolution for Motion Planning of Multiple Robotic Manipulators
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We address the motion planning problem for multiple robotic manipulators in packed environments where shared workspace can result in goal positions occupied or blocked by other robots unless those other robots move away to make the goal positions free. While planning in a coupled configuration space (C-space) is straightforward, it struggles to scale with the number of robots and often fails to find solutions. Decoupled planning is faster but frequently leads to conflicts between trajectories. We propose a conflict resolution approach that inserts pauses into individually planned trajectories using an A* search strategy to minimize the makespan--the total time until all robots complete their tasks. This method allows some robots to stop, enabling others to move without collisions, and maintains short distances in the C-space. It also effectively handles cases where goal positions are initially blocked by other robots. Experimental results show that our method successfully solves challenging instances where baseline methods fail to find feasible solutions.
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Cited by 1 Pith paper
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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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