6 accepted papers
This letter proposes a novel and simple smooth path generation algorithm for autonomous vehicles. The proposed method can rapidly generate feasible and curvature continuous paths connecting any two given states with null curvature. The generated path comprises straight lines, circular arcs and cloth
Velocity planning is an important module of autonomous driving, which aims to generate the velocity profile given a reference path. However, most existing algorithms fail to adequately address the uncertainty inherent in driving contexts, leading to potentially risky situations. To this end, we prop
Planning and prediction are two important modules of autonomous driving and have experienced tremendous advancement recently. Nevertheless, most existing methods regard planning and prediction as independent and ignore the correlation between them, leading to the lack of consideration for interactio…
Local planning for a differential wheeled robot is designed to generate kinodynamic feasible actions that guide the robot to a goal position along the navigation path while avoiding obstacles. Reactive, predictive, and learning-based methods are widely used in local planning. However, few of them ca
Collision risk and smoothness are the most important factors in global path planning. Currently, planning methods that reduce global path collision risk and improve its smoothness through numerical optimization have achieved good results. However, these methods cannot always optimize the path. The r…
The path planning of mobile robots is an optimization problem that is difficult to solve directly owing to its nonlinear characteristics. This letter proposes the “global-local” Coupling Two-Stage Path Planning (CTSP) method. First, the globally optimal solution in the configuration space is given b