To achieve optimal robot behavior in dynamic scenarios we need to consider complex
dynamics in a predictive manner. In the vehicle dynamics community, it is well know that to …

Driving on the limits of vehicle dynamics requires predictive planning of future vehicle states.
In this work, a search-based motion planning is used to generate suitable reference …

Robots are required to perform more and more complicated tasks, which raises the
requirement of more intelligent planning algorithms. As a domain having been explored for …

Many autonomous driving motion planners generate trajectories by optimizing a reward/cost
functional. Designing and tuning a high-performance reward/cost functional for Level-4 …

This paper presents a framework for fast and robust motion planning designed to facilitate
automated driving. The framework allows for real-time computation even for horizons of …

Predictive motion planning is the key to achieve energy-efficient driving, which is one of the
main benefits of automated driving. Researchers have been studying the planning of …

Combined Task and Motion Planning (TAMP) is an area where no one-fits-all solution can
exist. Many aspects of the domain, as well as operational requirements, have an effect on …

This paper presents a novel algorithm for robot task and motion planning (TAMP) problems
by utilizing a reachability tree. While tree-based algorithms are known for their speed and …

This letter presents a hierarchical motion planner for generating smooth and feasible
trajectories for autonomous vehicles in unstructured environments with static and moving …

Numerical experiments for motion planning of road vehicles require numerous components:
vehicle dynamics, a road network, static obstacles, dynamic obstacles and their movement …