位置・トルク制御ヒューマノイド歩行のためのオンライン予測計画を備えた制御アーキテクチャ
A Control Architecture with Online Predictive Planning for Position and Torque Controlled Walking of Humanoid Robots
足位置計画・予測制御・QPベースのトルク制御を3層に組み合わせ、位置制御とトルク制御の両方でヒューマノイドiCubを歩行させた研究。
著者: Stefano Dafarra, Gabriele Nava, Marie Charbonneau, Nuno Guedelha, Francisco Andrade, Silvio Traversaro, Luca Fiorio, Francesco Romano, Francesco Nori, Giorgio Metta, Daniele Pucci
分類: cs.RO
原文アブストラクト
A common approach to the generation of walking patterns for humanoid robots consists in adopting a layered control architecture. This paper proposes an architecture composed of three nested control loops. The outer loop exploits a robot kinematic model to plan the footstep positions. In the mid layer, a predictive controller generates a Center of Mass trajectory according to the well-known table-cart model. Through a whole-body inverse kinematics algorithm, we can define joint references for position controlled walking. The outcomes of these two loops are then interpreted as inputs of a stack-of-task QP-based torque controller, which represents the inner loop of the presented control architecture. This resulting architecture allows the robot to walk also in torque control, guaranteeing higher level of compliance. Real world experiments have been carried on the humanoid robot iCub.
