2 citations · 2 across the 8 of their papers we have counts for
5 papers · 2 filters
A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics
Puze Liu, Jonas Günster, Niklas Funk +17
Machine learning methods have a groundbreaking impact in many application domains, but their application on real robotic platforms is still limited. Despite the many challenges ass…
Distilling Contact Planning for Fast Trajectory Optimization in Robot Air Hockey
Julius Jankowski, Ante Marić, Puze Liu +3
Robot control through contact is challenging as it requires reasoning over long horizons and discontinuous system dynamics. Highly dynamic tasks such as Air Hockey additionally req…
Robust Pushing: Exploiting Quasi-static Belief Dynamics and Contact-informed Optimization
Julius Jankowski, Lara Brudermüller, Nick Hawes +1
Non-prehensile manipulation such as pushing is typically subject to uncertain, non-smooth dynamics. However, modeling the uncertainty of the dynamics typically results in intractab…
CC-VPSTO: Chance-Constrained Via-Point-Based Stochastic Trajectory Optimisation for Online Robot Motion Planning under Uncertainty
Lara Brudermüller, Guillaume Berger, Julius Jankowski +3
Reliable robot autonomy hinges on decision-making systems that account for uncertainty without imposing overly conservative restrictions on the robot's action space. We introduce C…
AiRLIHockey: Highly Reactive Contact Control and Stochastic Optimal Shooting
Julius Jankowski, Ante Marić, Sylvain Calinon
Air hockey is a highly reactive game which requires the player to quickly reason over stochastic puck and contact dynamics. We implement a hierarchical framework which combines sto…