Abstract:

This paper develops an invariant-set motion- planner (ISMP) for vehicles with unicycle-like dynamics. ISMPs operate by determining a sequence of obstacle-free positively invariant (PI) sets for the closed-loop system that connect the initial and target state. In this paper, we derive PI sets under a dynamic feedback linearization law. We demonstrate that the PI sets are simple in geometry and we provide an efficient algorithm for obstacle-free scaling. The PI sets are then used to develop a graph-based search for finding an obstacle-free path between two states. The approach is demonstrated in an obstacle-rich simulated environment.