砂地でのロボット歩行シミュレーション：オープンソース物理エンジンにおける抵抗体力理論
Simulating Robotic Locomotion in Sand: Resistive Force Theory in an Open-Source Physics Engine
砂地でのロボット歩行をシミュレートするため、抵抗体力理論を物理エンジンMuJoCoに実装し、12自由度ヘキサポッドロボットの歩行距離と足の沈み込みを実験の20%以内で予測できることを示した。
著者: Ryan Walker Brown, Laura K. Treers, Kathryn A. Daltorio
分類: cs.RO, eess.SY
原文アブストラクト
Recent advancements in Resistive Force Theory (RFT) enable approximation of ground reaction forces for locomotion in sand without the computational expense of modeling interactions with individual grains. However, these tools have been absent in 3D physics engines commonly used for robot simulation. We explore if resistive force approximations are sufficient, when integrated with standard dynamics calculations, to provide a stable substrate for a freely walking robot. To determine this, we implement 3D Granular Resistive Force Theory (3D RFT) in a physics simulation engine, MuJoCo. We verify simulations in multiple scenarios to demonstrate that key trends due to end effector shape, speed, and loading are preserved. Our implementation predicts walking distance and foot sinkage of a 12-Degree of Freedom hexapod robot within 20\% of experiments in sand. While RFT has inherent approximations, the open source tool described here has potential to help develop new and improved robot designs to traverse granular media substrates.