逆運動学を低ランクユークリッド距離行列補完として解く
Inverse Kinematics as Low-Rank Euclidean Distance Matrix Completion
剛体付着点間の距離行列でロボットの運動学を表し、逆運動学を低ランク行列補完問題としてリーマン最適化で解く手法を提案した。
著者: Filip Marić, Matthew Giamou, Ivan Petrović, Jonathan Kelly
分類: cs.RO
原文アブストラクト
The majority of inverse kinematics (IK) algorithms search for solutions in a configuration space defined by joint angles. However, the kinematics of many robots can also be described in terms of distances between rigidly-attached points, which collectively form a Euclidean distance matrix. This alternative geometric description of the kinematics reveals an elegant equivalence between IK and the problem of low-rank matrix completion. We use this connection to implement a novel Riemannian optimization-based solution to IK for various articulated robots with symmetric joint angle constraints.
