4 accepted papers
Long-horizon planning is crucial in complex environments, but diffusion-based planners like Diffuser are limited by the trajectory lengths observed during training. This creates a dilemma: long trajectories are needed for effective planning, yet they degrade model performance. In this paper, we intr
Stochastic policy-based deep reinforcement learning (RL) approaches have remarkably succeeded to deal with continuous control tasks. However, applying these methods to manipulation tasks remains a challenge since actuators of a robot manipulator require high dimensional continuous action spaces. In…
In this paper, we propose a probabilistic collision threat assessment algorithm for autonomous driving at road intersections that assesses a given traffic situation at an intersection reliably and robustly for an autonomous vehicle to cross the intersection safely, even in the face of violation vehi…
This paper presents a risk assessment algorithm for automatic lane change maneuvers on highways. It is capable of reliably assessing a given highway situation in terms of the possibility of collisions and robustly giving a recommendation for lane changes. The algorithm infers potential collision ris…