PATACON: 拘束付き動作計画のためのGPU並列接束RRT-Connect
PATACON: GPU-Parallel Tangent-Bundle RRT-Connect for Constrained Motion Planning
拘束多様体の接空間をGPUで並列探索する双方向動作計画器を提案し、高次元の全身拘束計画で最大11.25倍の高速化を実現した。
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著者: Gahyun Oh, Junho An, Suhyun Jeon, Suhan Park
分類: cs.RO
原文アブストラクト
Fast whole-body motion planning enables continuous replanning for humanoid robots in dynamic environments while satisfying collision avoidance and kinematic constraints. However, constrained motion planning incurs substantial computational cost due to repeated constraint projection in addition to collision checking and nearest-neighbor search. Recently, GPU-based massively parallel planners have been proposed to reduce computational cost. Nevertheless, these planners still steer in the ambient configuration space, so projecting candidates that deviate from the manifold remains a significant source of overhead, particularly in highly constrained, high-dimensional problems. In this work, we introduce PATACON, a GPU-parallel bidirectional planner that explores tangent space to exploit the local manifold geometry induced by known constraint functions. Experiments on dual-arm closed-chain and humanoid whole-body constrained planning tasks show that PATACON outperforms the prior work as configuration-space dimension and constraint codimension grow, achieving up to an 11.25 times speedup. These results suggest that GPU-parallel tangent-space exploration brings constrained whole-body motion planning closer to real-time performance.