確率的安全プログラム：不確実性下での安全制御フレームワーク
Probabilistic Safety Programs
環境の不確実性と安全不変条件を組み込んだ確率的プログラムをグラフィカルモデルに変換し、変異推論で将来行動の安全性を高速評価する手法を提案。ドローンや自動運転車の安全制御で有効性を示した。
著者: Ashish Kapoor, Debadeepta Dey, Shital Shah
分類: cs.RO
原文アブストラクト
Achieving safe control under uncertainty is a key problem that needs to be tackled for enabling real-world autonomous robots and cyber-physical systems. This paper introduces Probabilistic Safety Programs (PSP) that embed both the uncertainty in the environment as well as invariants that determine safety parameters. The goal of these PSPs is to evaluate future actions or trajectories and determine how likely it is that the system will stay safe under uncertainty. We propose to perform these evaluations by first compiling the PSP to a graphical model then using a fast variational inference algorithm. We highlight the efficacy of the framework on the task of safe control of quadrotors and autonomous vehicles in dynamic environments.
