単一プランナで実現する多様なヒューマノイド移動
A Single-Planner Approach to Multi-Modal Humanoid Mobility
歩行・這い・登攀など複数の移動様式を一つの探索プロセスで統合的に計画し、実行と並行して動かせるプランナを提案した論文。
著者: Andrew Dornbush, Karthik Vijayakumar, Sameer Bardapurkar, Fahad Islam, Maxim Likhachev
分類: cs.RO
原文アブストラクト
In this work, we present an approach to planning for humanoid mobility. Humanoid mobility is a challenging problem, as the configuration space for a humanoid robot is intractably large, especially if the robot is capable of performing many types of locomotion. For example, a humanoid robot may be able to perform such tasks as bipedal walking, crawling, and climbing. Our approach is to plan for all these tasks within a single search process. This allows the search to reason about all the capabilities of the robot at any point, and to derive the complete solution such that the plan is guaranteed to be feasible. A key observation is that we often can roughly decompose a mobility task into a sequence of smaller tasks, and focus planning efforts to reason over much smaller search spaces. To this end, we leverage the results of a recently developed framework for planning with adaptive dimensionality, and incorporate the capabilities of available controllers directly into the planning process. The resulting planner can also be run in an interleaved fashion alongside execution so that time spent idle is much reduced.
