可動障害物を押しのけて進むアフォーダンスベースの移動ロボットナビゲーション
Affordance-Based Mobile Robot Navigation Among Movable Obstacles
障害物の可動性をアフォーダンスとして認識し、接触を許容する軌道最適化で押しのけながら目的地へ移動する枠組みを提案し、HSRで実機検証した。
著者: Maozhen Wang, Rui Luo, Aykut Ozgun Onol, Taskin Padir
分類: cs.RO
原文アブストラクト
Avoiding obstacles in the perceived world has been the classical approach to autonomous mobile robot navigation. However, this usually leads to unnatural and inefficient motions that significantly differ from the way humans move in tight and dynamic spaces, as we do not refrain interacting with the environment around us when necessary. Inspired by this observation, we propose a framework for autonomous robot navigation among movable obstacles (NAMO) that is based on the theory of affordances and contact-implicit motion planning. We consider a realistic scenario in which a mobile service robot negotiates unknown obstacles in the environment while navigating to a goal state. An affordance extraction procedure is performed for novel obstacles to detect their movability, and a contact-implicit trajectory optimization method is used to enable the robot to interact with movable obstacles to improve the task performance or to complete an otherwise infeasible task. We demonstrate the performance of the proposed framework by hardware experiments with Toyota's Human Support Robot.
