Generalist robot policies are trained with imitation learning and are bounded by the quality and coverage of their demonstrations. Reinforcement learning can improve and extend them, either by fine-tuning the policy weights or by training a small module to steer the input noise of a frozen generative policy. When tasks...
Bahey Tharwat, Iman Nematollahi, Marvin Alles et al.· 0 citations
Self-play in high-throughput simulators yields driving policies with robust closed-loop performance, but improvement per unit of simulation diminishes as training scales. Policies learn to handle common situations early, while further rollouts repeatedly encounter unresolved failures. Post-training offers an opportunit...
Jia-Rong Wei, Yi-Nuo Wu, Runkai He et al.· 0 citations
Latent world models learn predictive representations for autonomous driving, but the relational semantics these states preserve often remain implicit. We investigate whether traffic scene graphs can serve as privileged semantic supervision for latent world representations. Building on LAW, we construct actor-centric sc...
Fabian Schmidt, Markus Enzweiler, Abhinav Valada· 0 citations
Advances in generative modeling have recently been extensively employed in robotics for policy learning. In particular, Conditional Flow Matching (CFM) trained with expert demonstrations has been shown to outperform existing methods on robot manipulation benchmarks. While prior work has mainly focused on single-task se...
Shreya Deshmukh, Imen Mahdi, Nick Heppert et al.· 0 citations
Care robots are increasingly being introduced into healthcare settings, raising important questions about their acceptance and ethical implementation. To better understand these challenges, this study investigates caregivers'perceptions of four categories of care robots: delivering supplies, helping patients into bed,...
Laura Londoño, Klaus Baumann, A. Valada et al.· 0 citations
GhostPoint is proposed, an SSL framework that hallucinates latent features in local neighborhoods around discovered instances, generated via a novel instance voxel dilation, and introduces a predictor-level supervision scheme on sampled voxels from generated neighborhoods.
Mohamed Abdelsamad, Bin Yang, Michael Ulrich et al.· 1 citation
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