Abstract
Dynamic window approach (DWA) is one of the most widely used algorithms for local path planning and autonomous navigation. Although many successful examples have been shown under various operation conditions, to the authors' best knowledge, there is a lack of systematic reliability analysis, its further design improvement, and systems operation guidelines for meeting reliability requirement under different operation conditions. Several goals can be defined for a successful path planning and autonomous navigation. Among them, assurance of the collision avoidance and reaching the goal with less time are pivotal requirements, yet such reliability analysis is rarely conducted in a rigorous manner. Furthermore, design improvement and systems operation design based on rigorous reliability analysis can hardly be found in this area. This paper addresses such a research gap for autonomous navigation reliability analysis and further conducts design improvement and characterizes systems operation conditions for meeting the collision avoidance reliability using the DWA. To address the technical challenges associated with limited number of simulations or experiments, reliability analysis is conducted using Bayesian statistics combined with the Monte Carlo simulation (MCS). Design improvement and reliable operation conditions can then be conducted based on the reliability analysis. Results indicate that performance reliability of the DWA is sensitive to its parameter configuration, which can be improved through reliability-based design optimization. With characterized collision avoidance reliability constraints, performance reliability of the DWA can be ensured through adjusting its operation parameters.
