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cs.RO2026
Find Something You Can't Do: Agentic Real-World Reinforcement Learning for Self-Improving VLA Models
Yuan Fang, Zechu Li, Haolei Tong +2
Vision--language--action (VLA) models provide strong priors for robotic manipulation but are typically deployed as frozen policies, unable to improve from their own failures. Real-…
cs.RO2025
Adaptive Diffusion Constrained Sampling for Bimanual Robot Manipulation
Haolei Tong, Yuezhe Zhang, Sophie Lueth +1
Coordinated multi-arm manipulation requires satisfying multiple simultaneous geometric constraints across high-dimensional configuration spaces, which poses a significant challenge…
cs.RO2025
Constrained Gaussian Process Motion Planning via Stein Variational Newton Inference
Jiayun Li, Kay Pompetzki, An Thai Le +3
Gaussian Process Motion Planning (GPMP) is a widely used framework for generating smooth trajectories within a limited compute time--an essential requirement in many robotic applic…