CoRL

Generalist Robot Manipulation beyond Action Labeled Data

Alexander Spiridonov, Jan-Nico Zaech, Nikolay Nikolov, Luc Van Gool, Danda Pani Paudel

机构 * ETH Zurich, Switzerland（苏黎世联邦理工学院，瑞士） 纠错

Comments Accepted at Conference on Robot Learning 2025

EgoBridge: Domain Adaptation for Generalizable Imitation from Egocentric Human Data

Ryan Punamiya, Dhruv Patel, Patcharapong Aphiwetsa, Pranav Kuppili, Lawrence Y. Zhu, Simar Kareer, Judy Hoffman, Danfei Xu

机构 * Georgia Institute of Technology（佐治亚理工学院） 纠错

Comments Accepted at 39th Conference on Neural Information Processing Systems (NeurIPS 2025) and Oral at Conference on Robot Learning (CoRL 2025)

From Space to Time: Enabling Adaptive Safety with Learned Value Functions via Disturbance Recasting

Sander Tonkens, Nikhil Uday Shinde, Azra Begzadić, Michael C. Yip, Jorge Cortés, Sylvia L. Herbert

机构 * University of California San Diego（加州大学圣地亚哥分校） 纠错

Comments The first three authors contributed equally. This work has been accepted for publication at the Conference on Robot Learning

Score the Steps, Not Just the Goal: VLM-Based Subgoal Evaluation for Robotic Manipulation

Ramy ElMallah, Krish Chhajer, Chi-Guhn Lee

机构 * University of Toronto（多伦多大学） 纠错

Comments Accepted to the CoRL 2025 Eval&Deploy Workshop

CUPID: Curating Data your Robot Loves with Influence Functions

Christopher Agia, Rohan Sinha, Jingyun Yang, Rika Antonova, Marco Pavone, Haruki Nishimura, Masha Itkina, Jeannette Bohg

机构 * Stanford University（斯坦福大学） ； University of Cambridge（剑桥大学） ； NVIDIA Research（NVIDIA研究） ； Toyota Research Institute（丰田研究机构） 纠错

Comments Project page: https://cupid-curation.github.io. 27 pages, 15 figures. Accepted to the Conference on Robot Learning (CoRL) 2025

Uncertainty-aware Latent Safety Filters for Avoiding Out-of-Distribution Failures

Junwon Seo, Kensuke Nakamura, Andrea Bajcsy

Comments Conference on Robot Learning (CoRL 2025)