5 papers
Visual Action Planning with Multiple Heterogeneous Agents
Martina Lippi, Michael C. Welle, Marco Moletta +3
Visual planning methods are promising to handle complex settings where extracting the system state is challenging. However, none of the existing works tackles the case of multiple…
Low-Cost Teleoperation with Haptic Feedback through Vision-based Tactile Sensors for Rigid and Soft Object Manipulation
Martina Lippi, Michael C. Welle, Maciej K. Wozniak +2
Haptic feedback is essential for humans to successfully perform complex and delicate manipulation tasks. A recent rise in tactile sensors has enabled robots to leverage the sense o…
A Robotic Skill Learning System Built Upon Diffusion Policies and Foundation Models
Nils Ingelhag, Jesper Munkeby, Jonne van Haastregt +3
In this paper, we build upon two major recent developments in the field, Diffusion Policies for visuomotor manipulation and large pre-trained multimodal foundational models to obta…
Enabling Robot Manipulation of Soft and Rigid Objects with Vision-based Tactile Sensors
Michael C. Welle, Martina Lippi, Haofei Lu +3
Endowing robots with tactile capabilities opens up new possibilities for their interaction with the environment, including the ability to handle fragile and/or soft objects. In thi…
Ensemble Latent Space Roadmap for Improved Robustness in Visual Action Planning
Martina Lippi, Michael C. Welle, Andrea Gasparri +1
Planning in learned latent spaces helps to decrease the dimensionality of raw observations. In this work, we propose to leverage the ensemble paradigm to enhance the robustness of…