This paper presents a guide path-free multimodal trajectory planning framework for autonomous surface vehicles operating in dynamic environments that alleviates the local-minimum and deadlock problems of single-mode MPC while maintaining computational efficiency.
This paper presents a fast adaptive planning method for tractor-trailer systems that resolves parameter uncertainties by adapting a nominal trajectory to true parameters via iLQR, eliminating the need to store MPs for various configurations.
High-precision control of heavy-duty autonomous ground vehicles (AGVs) in cluttered factories requires paths that account for the full vehicle–cargo envelope and numerically reliable reference trajectories across widely varying segment durations. This paper presents a two-stage planning and reference-generation framewo...
The proposed Turn-Deviation Optimized Multi-Stage Framework (TDO-MSF) improves trajectory smoothness and obstacle-avoidance performance while maintaining curvature-constrained and trajectory-guided obstacle-avoidance capabilities.
Autonomous racecars operate at the limits of vehicle dynamics, where small control errors translate into safety-critical behavior and lost performance. Trajectory planners assume perfect tracking and remain blind to execution errors. To guarantee safety, trajectory planners therefore restrict themselves to conservative...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
