Complex manipulation tasks require careful integration of symbolic reasoning and motion
planning. This problem, commonly referred to as Task and Motion Planning (TAMP), is even …

We present a motion planner for autonomous on-road driving, especially on highways. It
adapts the idea of a on-road state lattice. A focused search is performed in the previously …

We propose a motion planning method for automated vehicles (AVs) to complete driving
tasks in dynamic traffic scenes. The proposed method aims to generate motion trajectories …

Safe and adaptable motion planning for autonomous vehicles remains an open problem in
urban environments, where the variability of situations and behaviors may become …

Motion planners for autonomous vehicles often involve a two-level hierarchical structure
consisting of a high-level, discrete planner and a low-level trajectory generation scheme. To …

Trajectory planning at high velocities and at the handling limits is a challenging task. In order
to cope with the requirements of a race scenario, we propose a far-sighted two step, multi …

Motion planning as trajectory optimization requires generating trajectories that minimize a
desired objective function or performance metric. Finding a globally optimal solution is often …

Motion planning of automated vehicles requires dynamical models to ensure that obtained
trajectories are drivable. An often overlooked aspect is that motion planning is usually done …

The nonlinear vehicle dynamics and the non-convexity of collision avoidance constraints
pose major challenges for optimization-based trajectory planning of automated vehicles …

Trajectory planning is an important component of autonomous driving. It takes the result of
route-level navigation plan and generates the motion-level commands that steer an …