混合整数錐計画法による大域的最適把持計画の新定式化
New Formulation of Mixed-Integer Conic Programming for Globally Optimal Grasp Planning
グリッパの運動学的実現可能性を考慮しつつ把持品質を最大化する最適把持姿勢を求める二段階分枝限定法を提案し、逆運動学を少数の二値変数で表す新しい混合整数錐計画法の定式化により効率的に解く。
著者: Min Liu, Zherong Pan, Kai Xu, Dinesh Manocha
分類: cs.RO
原文アブストラクト
We present a two-level branch-and-bound (BB) algorithm to compute the optimal gripper pose that maximizes a grasp metric in a restricted search space. Our method can take the gripper's kinematics feasibility into consideration to ensure that a given gripper can reach the set of grasp points without collisions or predict infeasibility with finite-time termination when no pose exists for a given set of grasp points. Our main technical contribution is a novel mixed-integer conic programming (MICP) formulation for the inverse kinematics of the gripper that uses a small number of binary variables and tightened constraints, which can be efficiently solved via a low-level BB algorithm. Our experiments show that optimal gripper poses for various target objects can be computed taking 20-180 minutes of computation on a desktop machine and the computed grasp quality, in terms of the Q1 metric, is better than those generated using sampling-based planners.
