Gibbs Sampler-Based Path Planning for Autonomous Vehicles: Convergence Analysis
Abstract
Simulation has indicated that distributed self-organization of autonomous swarms might be achieved through Gibbs sampler-based simulated annealing. However, the dynamic nature of the underlying graph presents significant challenges in convergence analysis. As a first step toward such analysis, convergence of the algorithm is established in this paper for two special cases: single vehicle with limited sensing/moving range, and multiple vehicles with full sensing/moving range. The impact of Gibbspotential functions on the convergence speed is also investigated, which provides insight into the design of these functions.
