cuRoboV2-Fast：高速なトルク制限付き衝突回避動作計画
cuRoboV2-Fast: Fast Torque-Limited Collision-Free Motion Planning
GPU加速により、衝突回避・ペイロード考慮・トルク制限付きの動作計画を高速化し、計画時間と実行時間を大幅に短縮したプランナを提案。
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著者: Balakumar Sundaralingam, Adithyavairavan Murali, Stan Birchfield
分類: cs.RO
原文アブストラクト
We present cuRoboV2-Fast, a GPU-accelerated planner that reduces both planning latency and execution time for collision-free, payload-aware, torque-limited motions. B-spline trajectory optimization reduces the required iterations, while accelerated robot computations and differentiable inverse dynamics reduce refinement cost and accommodate changing payloads. TimeOpt optimizes traversal speed along the fixed path under sampled velocity, acceleration, jerk, and torque constraints, exploiting local spline support to solve banded Newton systems efficiently on the GPU. With a 3,kg payload, cuRoboV2-Fast achieves 4.4 ms mean planning time on RTX 5090, 14.7x faster than cuRoboV2. Our method on Jetson AGX Orin plans faster than cuRoboV1 + TOPPRA on RTX 5090. A stereo-camera-based deployment on YAM achieves 5.93 s mean completed pick-and-drop cycles, 34.6% shorter than cuRoboV2. Code (Apache 2.0): www.github.com/NVlabs/curobo , Project Page: www.research.nvidia.com/labs/lpr/curobov2-fast .