Safe Sequential Path Planning Under Disturbances and Imperfect Information
For multi-UAV safety-critical systems, this work makes SPP more practical by addressing real-world imperfections, though it is an incremental extension of prior work.
This paper extends sequential path planning (SPP) for multi-UAV systems to handle disturbances and imperfect information, proposing three methods with different information-sharing assumptions. Simulations demonstrate the effectiveness of the approaches.
Multi-UAV systems are safety-critical, and guarantees must be made to ensure no unsafe configurations occur. Hamilton-Jacobi (HJ) reachability is ideal for analyzing such safety-critical systems; however, its direct application is limited to small-scale systems of no more than two vehicles due to an exponentially-scaling computational complexity. Previously, the sequential path planning (SPP) method, which assigns strict priorities to vehicles, was proposed; SPP allows multi-vehicle path planning to be done with a linearly-scaling computational complexity. However, the previous formulation assumed that there are no disturbances, and that every vehicle has perfect knowledge of higher-priority vehicles' positions. In this paper, we make SPP more practical by providing three different methods to account for disturbances in dynamics and imperfect knowledge of higher-priority vehicles' states. Each method has different assumptions about information sharing. We demonstrate our proposed methods in simulations.