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Search-Based Conflict Resolution for Motion Planning of Multiple Robotic Manipulators

초록 (요약문)

In this thesis, we consider the motion planning problem of multiple robotic manipulators that work in packed environments while sharing a large portion of their workspace. We are particularly interested in instances where some goal positions are occupied or blocked by other manipulators unless those other manipulators move away to make the goal positions free. While planning their trajectories in a coupled (or composite) configuration space (C-space) of all manipulators is the simplest, it could not be able to find a solution and does not scale in the number of manipulators. Decoupling the C-space can achieve faster planning but frequently results in numerous conflicts between the individually planned trajectories. We propose an approach to resolve conflicts by inserting pauses into individually planned trajectories using an A∗ search strategy, aimed at minimizing the makespan of the entire execution. In other words, our method allows some manipulators to stop appropriately to enable other manipulators to move without collisions. While this temporal adjustment might introduce delays, it allows the trajectories to be executed without modifications in the C-space, thereby maintaining short distances. Another advantage is the ability to plan even when some goal positions are initially unreachable due to other manipulators. Experimental results demonstrate that our method can solve such challenging in- stances where baseline methods fail to find any feasible solution.

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초록 (요약문)

본 논문에서는 다수 매니퓰레이터 로봇 간 발생할 수 있는 간섭을 각 로봇의 모션 경로에 일시적인 기다리는 모션을 추가하여 해소하는 방법을 제안한다. 다수 매니퓰레이터는 협소한 공간에서 공동 작업을 수행할 때 목표 위치가 다른 로봇에 의해 점유되거나 차단되는 상황이 빈번하게 발생한다. 다수 매니퓰레이터의 모션 계획 기술로 전체 로봇에 대한 구성공간 (configuration space) 에서 동기화된 모션 계획을 실시하는 방법이 있지만, 충돌이 발생하지 않는 유효한 구성공간이 좁은 경 우 충돌 없는 모션을 찾는 데 실패하거나 오랜 시간이 걸릴 수 있다는 문제가 있다.

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목차

1 Introduction 1
2 Related works 5
3 Problem Description 7
4 Proposed Method 9
4.1 Overview 9
4.2 Stop-N-Go algorithm 12
4.3 Conflict Resolution 15
4.4 Analysis of Stop-N-Go algorithm 21
5 Experiments 24
6 Conclusion 33
Bibliography 34

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