距離関数を近似する区分線形回帰データ構造
Piecewise linear regressions for approximating distance metrics
ロボットの配置空間上の距離を二分空間分割と局所線形近似で要約するデータ構造を提案し、単一ロボット用に構築した構造をマルチロボット運動計画のヒューリスティックとして活用する。
著者: Josiah Putman, Lisa Oh, Luyang Zhao, Evan Honnold, Galen Brown, Weifu Wang, Devin Balkcom
分類: cs.RO, cs.AI
原文アブストラクト
This paper presents a data structure that summarizes distances between configurations across a robot configuration space, using a binary space partition whose cells contain parameters used for a locally linear approximation of the distance function. Querying the data structure is extremely fast, particularly when compared to the graph search required for querying Probabilistic Roadmaps, and memory requirements are promising. The paper explores the use of the data structure constructed for a single robot to provide a heuristic for challenging multi-robot motion planning problems. Potential applications also include the use of remote computation to analyze the space of robot motions, which then might be transmitted on-demand to robots with fewer computational resources.
