BiConMP：全身運動計画のための非線形モデル予測制御フレームワーク
BiConMP: A Nonlinear Model Predictive Control Framework for Whole Body Motion Planning
ロボットの動力学構造を効率的に活用し、脚式ロボットの全身軌道をオンライン生成する非線形MPCフレームワークBiConMPを提案。実機四足ロボットで周期歩容や不整地・外乱対応、歩容遷移を実証し、ヒューマノイドや別の四足ロボットのシミュレーションでも動的運動生成を検証した。
著者: Avadesh Meduri, Paarth Shah, Julian Viereck, Majid Khadiv, Ioannis Havoutis, Ludovic Righetti
分類: cs.RO
原文アブストラクト
Online planning of whole-body motions for legged robots is challenging due to the inherent nonlinearity in the robot dynamics. In this work, we propose a nonlinear MPC framework, the BiConMP which can generate whole body trajectories online by efficiently exploiting the structure of the robot dynamics. BiConMP is used to generate various cyclic gaits on a real quadruped robot and its performance is evaluated on different terrain, countering unforeseen pushes and transitioning online between different gaits. Further, the ability of BiConMP to generate non-trivial acyclic whole-body dynamic motions on the robot is presented. The same approach is also used to generate various dynamic motions in MPC on a humanoid robot (Talos) and another quadruped robot (AnYmal) in simulation. Finally, an extensive empirical analysis on the effects of planning horizon and frequency on the nonlinear MPC framework is reported and discussed.
