Receding Horizon Control for Signal Temporal Logic Using Robustness-Conserving Partial Formula Evaluation

Abstract

We present a bounded-memory receding horizon approach to robot control for complex specifications in dynamic environments. We use Signal Temporal Logic, a logic that quantifies how robustly trajectories satisfy the specification, to specify robot behavior. To handle unbounded specifications, we consider a short planning horizon, only searching for nonviolating trajectories. We identify the subset of Signal Temporal Logic for which this approach needs only a bounded memory of the past, and leverage syntactic separation to summarize the robust satisfaction of the trajectory as it evolves. We implement our approach using receding horizon control in dynamic environments. We demonstrate the effectiveness and scalability of our approach compared to the state-of-the-art approach in several case studies.