3 papers
cs.RO2026
Any2Any: Efficient Cross-Embodiment Transfer for Humanoid Whole-Body Tracking
Ming Yang, Tao Yu, Feng Li +1
Whole-body tracking (WBT) models have become a key foundation for humanoid robots, enabling them to imitate diverse motions with high fidelity. Training such models from scratch re…
cs.RO2026
Robo2Process: Benchmarking and Learning Process-Aware Understanding in Vision-Language Robotic Manipulation
Dayu Xia, Yue Shi, Yao Mu +7
Vision-language models (VLMs) used as robotic critics, reward generators, and failure detectors must understand how manipulation unfolds, not only whether it succeeds. Yet fine-gra…
cs.RO2026
Beyond Pixels: Learning Invariant Rewards for Real-World Robotics From a Few Demonstrations
Tengye Xu, Yangting Sun, Ziju Shen +5
Designing reward functions that generalize beyond controlled laboratory settings remains a fundamental challenge in reinforcement learning for robotics. In open-world manipulation…