Cost-Aware Path Planning Under Co-Safe Temporal Logic Specifications

This letter presents a path planning algorithm for generating a cost-efficient path that satisfies mission requirements specified in linear temporal logic (LTL). We assume that a cost function is defined over the configuration space. Examples of a cost function include hazard levels, wireless connectivity, and energy consumption, to name a few. The proposed method consists of two parts: sampling-based cost-aware path planning considering the vehicle dynamics based on rapidly-exploring random trees (RRT*), and a high-level logic which determines how to extend the RRT tree based on spatiotemporal specifications of an LTL formula. In order to find a low-cost trajectory with computational efficiency, the proposed method expands the RRT tree with long extensions using cross entropy, while the rewiring step of RRT* is used to preserve the asymptotic optimality. In simulation and experiments, we show that the proposed method performs favorably compared to existing methods.