8 papers
Intent-guided Adaptive Stiffening for Visuomotor Policies under Unknown Resistance
Francesco Cufino, Carmela Mariniello, Mario Selvaggio +2
Manipulation tasks such as unscrewing a cap or sliding a part in contact with a surface require imposing force along a high-friction direction: the robot must overcome a resistance…
Optimal Transport Q-Learning for Flow Policy Steering and Acceleration
Andreas Sochopoulos, Esmeralda S. Whitammer, Nikolaos Tsagkas +3
Diffusion and flow policies have recently demonstrated remarkable performance in robotic applications by accurately capturing multimodal robot trajectory distributions, especially…
Decoupling the Declarative from the Procedural in Vision-Language-Action Models
Nikolaos Tsagkas, Andreas Sochopoulos, Chris Xiaoxuan Lu +2
Deploying generalist robotic agents in the real world requires transferable skills. Specifically, a policy trained to clone a behavior from object-specific demonstrations must gene…
Attentive Feature Aggregation or: How Policies Learn to Stop Worrying about Robustness and Attend to Task-Relevant Visual Cues
Nikolaos Tsagkas, Andreas Sochopoulos, Duolikun Danier +4
The adoption of pre-trained visual representations (PVRs), leveraging features from large-scale vision models, has become a popular paradigm for training visuomotor policies. Howev…
Human-in-the-loop Optimisation in Robot-assisted Gait Training
Andreas Christou, Andreas Sochopoulos, Elliot Lister +1
Wearable robots offer a promising solution for quantitatively monitoring gait and providing systematic, adaptive assistance to promote patient independence and improve gait. Howeve…
Fast Flow-based Visuomotor Policies via Conditional Optimal Transport Couplings
Andreas Sochopoulos, Nikolay Malkin, Nikolaos Tsagkas +3
Diffusion and flow matching policies have recently demonstrated remarkable performance in robotic applications by accurately capturing multimodal robot trajectory distributions. Ho…
The Temporal Trap: Entanglement in Pre-Trained Visual Representations for Visuomotor Policy Learning
Nikolaos Tsagkas, Andreas Sochopoulos, Duolikun Danier +2
The integration of pre-trained visual representations (PVRs) has significantly advanced visuomotor policy learning. However, effectively leveraging these models remains a challenge…
Learning Deep Dynamical Systems using Stable Neural ODEs
Andreas Sochopoulos, Michael Gienger, Sethu Vijayakumar
Learning complex trajectories from demonstrations in robotic tasks has been effectively addressed through the utilization of Dynamical Systems (DS). State-of-the-art DS learning me…