ランダム化可能性グラフを用いた半非構造環境における足配置と全身動作の計画
Footstep and Motion Planning in Semi-unstructured Environments Using Randomized Possibility Graphs
制約多様体の高レベル近似で行動の可能性を高速探索し、全身動作を活用した二足歩行ロボットの足配置・動作計画を半非構造環境で実現する手法を提案。
著者: Michael X. Grey, Aaron D. Ames, C. Karen Liu
分類: cs.RO
原文アブストラクト
Traversing environments with arbitrary obstacles poses significant challenges for bipedal robots. In some cases, whole body motions may be necessary to maneuver around an obstacle, but most existing footstep planners can only select from a discrete set of predetermined footstep actions; they are unable to utilize the continuum of whole body motion that is truly available to the robot platform. Existing motion planners that can utilize whole body motion tend to struggle with the complexity of large-scale problems. We introduce a planning method, called the "Randomized Possibility Graph", which uses high-level approximations of constraint manifolds to rapidly explore the "possibility" of actions, thereby allowing lower-level motion planners to be utilized more efficiently. We demonstrate simulations of the method working in a variety of semi-unstructured environments. In this context, "semi-unstructured" means the walkable terrain is flat and even, but there are arbitrary 3D obstacles throughout the environment which may need to be stepped over or maneuvered around using whole body motions.
