時相論理制約下での共有自律ポリシー合成におけるパレート効率性
Pareto efficiency in synthesizing shared autonomy policies with temporal logic constraints
人間と自律制御器が制御権を共有する系をモデル化し、人間の負担と時相論理仕様の充足確率のトレードオフを考慮したパレート効率的な協調・制御ポリシーを二段階で合成する手法を提案した。
著者: Jie Fu, Ufuk Topcu
分類: cs.RO, cs.HC, cs.SY, eess.SY
原文アブストラクト
In systems in which control authority is shared by an autonomous controller and a human operator, it is important to find solutions that achieve a desirable system performance with a reasonable workload for the human operator. We formulate a shared autonomy system capable of capturing the interaction and switching control between an autonomous controller and a human operator, as well as the evolution of the operator's cognitive state during control execution. To trade-off human's effort and the performance level, e.g., measured by the probability of satisfying the underlying temporal logic specification, a two-stage policy synthesis algorithm is proposed for generating Pareto efficient coordination and control policies with respect to user specified weights. We integrate the Tchebychev scalarization method for multi-objective optimization methods to obtain a better coverage of the set of Pareto efficient solutions than linear scalarization methods.
