Optimal Planning and Control under Signal Temporal Logic Specifications
For roboticists and control engineers, this work addresses the challenge of integrating temporal logic specifications into motion planning, but the contribution appears incremental as it combines existing techniques (sampling-based planning, safe corridors) without a clear breakthrough.
This paper proposes a method for planning and control of nonlinear systems under Signal Temporal Logic (STL) specifications by decomposing tasks into local subtasks, generating waypoints via sampling, and constructing a safe corridor for optimization. Numerical examples demonstrate efficacy, but no concrete performance numbers are provided.
This paper addresses the planning and control problem for nonlinear systems under Signal Temporal Logic (STL) specifications. We first decompose an STL task into finite local tasks. A sampling-based method generates sequences of local waypoints to satisfy all local tasks, from which the corresponding satisfaction pair sets are derived. Following a local-to-global strategy, all sequences of local waypoints are synthesized into a global one, based on which a safe corridor is then constructed. Leveraging the safe corridor and the satisfaction pair sets, an optimization problem is formulated and solved to derive a position trajectory that satisfies the STL task. Finally, numerical examples and comparative results are presented to demonstrate the efficacy of the proposed approach.