階層型熟考・反応システムによる部分的既知環境でのタスク・動作計画
Technical Report: A Hierarchical Deliberative-Reactive System Architecture for Task and Motion Planning in Partially Known Environments
反応的ベクトル場プランナの到達保証を契約として活用し、熟考型サンプリング計画と組み合わせることで、未知障害物があっても計算コストを抑えつつ堅牢に計画できる階層型タスク・動作計画アーキテクチャを提案した。
著者: Vasileios Vasilopoulos, Sebastian Castro, William Vega-Brown, Daniel E. Koditschek, Nicholas Roy
分類: cs.RO
原文アブストラクト
We describe a task and motion planning architecture for highly dynamic systems that combines a domain-independent sampling-based deliberative planning algorithm with a global reactive planner. We leverage the recent development of a reactive, vector field planner that provides guarantees of reachability to large regions of the environment even in the face of unknown or unforeseen obstacles. The reachability guarantees can be formalized using contracts that allow a deliberative planner to reason purely in terms of those contracts and synthesize a plan by choosing a sequence of reactive behaviors and their target configurations, without evaluating specific motion plans between targets. This reduces both the search depth at which plans will be found, and the number of samples required to ensure a plan exists, while crucially preserving correctness guarantees. The result is reduced computational cost of synthesizing plans, and increased robustness of generated plans to actuator noise, model misspecification, or unknown obstacles. Simulation studies show that our hierarchical planning and execution architecture can solve complex navigation and rearrangement tasks, even when faced with narrow passageways or incomplete world information.
