5 citations · 15 across the 27 of their papers we have counts for
30 papers
Towards Safe Reinforcement Learning with Reduced Conservativeness: A Case Study on Drone Flight Control
Loizos Hadjiloizou, Michael C. Welle, Hang Yin +1
Incorporating formal methods into reinforcement learning (RL) has the potential to result in the best of both worlds, combining the robustness of formal guarantees with the adaptab…
One Body, Two Minds: Variable Autonomy Approach for a Co-embodied Robotic Hand
Piotr Koczy, Yuchong Zhang, Danica Kragic +1
Assistive robotic systems face a fundamental trade-off: fully autonomous systems lack user agency, while fully user-controlled systems demand continuous cognitive effort. Existing…
On the Generalization Capabilities, Design Choices and Limitations of Keypoint Imitation Learning
Thomas Lips, Marco Moletta, Michael C. Welle +2
RGB-based imitation learning requires many demonstrations to generalize to unseen objects or scenes, motivating research into intermediate representations to improve generalization…
Preference Aligned Visuomotor Diffusion Policies for Deformable Object Manipulation
Marco Moletta, Michael C. Welle, Danica Kragic
Humans naturally develop preferences for how manipulation tasks should be performed, which are often subtle, personal, and difficult to articulate. Although it is important for rob…
Hybrid Imitation Learning: Teleoperation Augmentation Primitives that Policies Learn to Trigger
Jonne Van Haastregt, Bastian Orthmann, Michael C. Welle +2
What an operator can demonstrate bounds what imitation learning can learn. Teleoperation interfaces map the human body to the robot, so motions that are hard for a human, such as h…
A Non-Adversarial Approach to Idempotent Generative Modelling
Mohammed Al-Jaff, Giovanni Luca Marchetti, Michael C Welle +5
Idempotent Generative Networks (IGNs) are deep generative models that also function as local data manifold projectors, mapping arbitrary inputs back onto the manifold. They are tra…