外乱と知覚品質変動に頑健な不整地歩行のためのヒューリスティック計画
Heuristic Planning for Rough Terrain Locomotion in Presence of External Disturbances and Variable Perception Quality
視覚情報が乏しい・劣化する状況でも4脚ロボットが不整地を歩けるよう、ヒューリスティックな計画手法と反射・外乱推定補償を組み合わせた枠組みを提案し、HyQで実証した。
著者: Michele Focchi, Romeo Orsolino, Marco Camurri, Victor Barasuol, Carlos Mastalli, Darwin G. Caldwell, Claudio Semini
分類: cs.RO
原文アブストラクト
The quality of the visual feedback can vary significantly on a legged robot that is meant to traverse unknown and unstructured terrains. The map of the environment, acquired with online state-of-the-art algorithms, often degrades after a few steps, due to sensing inaccuracies, slippage and unexpected disturbances. When designing locomotion algorithms, this degradation can result in planned trajectories that are not consistent with the reality, if not dealt properly. In this work, we propose a heuristic-based planning approach that enables a quadruped robot to successfully traverse a significantly rough terrain (e.g., stones up to 10 cm of diameter), in absence of visual feedback. When available, the approach allows also to exploit the visual feedback (e.g., to enhance the stepping strategy) in multiple ways, according to the quality of the 3D map. The proposed framework also includes reflexes, triggered in specific situations, and the possibility to estimate online an unknown time-varying disturbance and compensate for it. We demonstrate the effectiveness of the approach with experiments performed on our quadruped robot HyQ (85 kg), traversing different terrains, such as: ramps, rocks, bricks, pallets and stairs. We also demonstrate the capability to estimate and compensate for disturbances, showing the robot walking up a ramp while pulling a cart attached to its back.
