動的エージェントと相互作用するロボットの制御ポリシーの漸進的時相論理合成
Incremental Temporal Logic Synthesis of Control Policies for Robots Interacting with Dynamic Agents
時相論理仕様を満たすロボット制御ポリシーを、動的環境エージェントを段階的に追加しながら合成する漸進的手法を提案。計算資源の制約内で仕様充足確率を高める anytime アルゴリズム。
著者: Tichakorn Wongpiromsarn, Alphan Ulusoy, Calin Belta, Emilio Frazzoli, Daniela Rus
分類: cs.RO
原文アブストラクト
We consider the synthesis of control policies from temporal logic specifications for robots that interact with multiple dynamic environment agents. Each environment agent is modeled by a Markov chain whereas the robot is modeled by a finite transition system (in the deterministic case) or Markov decision process (in the stochastic case). Existing results in probabilistic verification are adapted to solve the synthesis problem. To partially address the state explosion issue, we propose an incremental approach where only a small subset of environment agents is incorporated in the synthesis procedure initially and more agents are successively added until we hit the constraints on computational resources. Our algorithm runs in an anytime fashion where the probability that the robot satisfies its specification increases as the algorithm progresses.
