多肢ロボットのフリークライミングを可能にする分散最適化による接触リッチな把持と移動の同時計画
Simultaneous Contact-Rich Grasping and Locomotion via Distributed Optimization Enabling Free-Climbing for Multi-Limbed Robots
多指把持を備えた多肢ロボットが、移動・把持・接触を同時に計画する分散最適化フレームワークを提案し、45度斜面のフリークライミングを実現した。
著者: Yuki Shirai, Xuan Lin, Alexander Schperberg, Yusuke Tanaka, Hayato Kato, Varit Vichathorn, Dennis Hong
分類: cs.RO, cs.AI, cs.SY, eess.SY
原文アブストラクト
While motion planning of locomotion for legged robots has shown great success, motion planning for legged robots with dexterous multi-finger grasping is not mature yet. We present an efficient motion planning framework for simultaneously solving locomotion (e.g., centroidal dynamics), grasping (e.g., patch contact), and contact (e.g., gait) problems. To accelerate the planning process, we propose distributed optimization frameworks based on Alternating Direction Methods of Multipliers (ADMM) to solve the original large-scale Mixed-Integer NonLinear Programming (MINLP). The resulting frameworks use Mixed-Integer Quadratic Programming (MIQP) to solve contact and NonLinear Programming (NLP) to solve nonlinear dynamics, which are more computationally tractable and less sensitive to parameters. Also, we explicitly enforce patch contact constraints from limit surfaces with micro-spine grippers. We demonstrate our proposed framework in the hardware experiments, showing that the multi-limbed robot is able to realize various motions including free-climbing at a slope angle 45{\deg} with a much shorter planning time.
