多脚壁登りロボットのための最適化ベース動作計画
Optimization Based Motion Planning for Multi-Limbed Vertical Climbing Robots
6脚ロボットが2枚の壁の間で摩擦のみの接触を保ちながら垂直登攀するための動作計画を、胴体姿勢と接触力に分離して最適化で解く手法を提案し、障害物や凹凸・傾斜壁で検証した。
著者: Xuan Lin, Jingwen Zhang, Junjie Shen, Gabriel Fernandez, Dennis W Hong
分類: cs.RO
原文アブストラクト
Motion planning trajectories for a multi-limbed robot to climb up walls requires a unique combination of constraints on torque, contact force, and posture. This paper focuses on motion planning for one particular setup wherein a six-legged robot braces itself between two vertical walls and climbs vertically with end effectors that only use friction. Instead of motion planning with a single nonlinear programming (NLP) solver, we decoupled the problem into two parts with distinct physical meaning: torso postures and contact forces. The first part can be formulated as either a mixed-integer convex programming (MICP) or NLP problem, while the second part is formulated as a series of standard convex optimization problems. Variants of the two wall climbing problem e.g., obstacle avoidance, uneven surfaces, and angled walls, help verify the proposed method in simulation and experimentation.
