From the 2 of 9 linked papers with an AI index.
7 papers · 1 filter
Learning Physical Interaction: A Survey of Tactile- and Force-aware Robot Learning
Shilin Shan, Chuhao Zhou, Ruize Wang +30
Physically grounded robot intelligence requires robots to perceive, reason about, and regulate their interactions with the physical world. This capability is particularly critical…
Representation-Aligned Tactile Grounding for Contact-Rich Robotic Manipulation
Ruilin Chen, Jingkai Jia, Tong Yang +8
The paper proposes a lightweight latent tactile predictor that aligns intermediate action representations with future tactile outcomes, improving contact-rich robotic manipulation…
GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch
GigaWorld Team, Angen Ye, Angyuan Ma +26
The paper introduces GigaWorld-Policy-0.5, a robot control model that learns from future visual dynamics during training but generates actions only at inference, achieving faster (…
GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation
GigaWorld Team, Angyuan Ma, Boyuan Wang +24
Evaluating embodied robot foundation models remains a critical bottleneck; unlike large language models efficiently assessed via digital benchmarks, robotic policies require slow,…
Diagnose, Correct, and Learn from Manipulation Failures via Visual Symbols
Xianchao Zeng, Xinyu Zhou, Youcheng Li +5
Vision-Language-Action (VLA) models have recently achieved remarkable progress in robotic manipulation, yet they remain limited in failure diagnosis and learning from failures. Add…
The Great March 100: 100 Detail-oriented Tasks for Evaluating Embodied AI Agents
Ziyu Wang, Chenyuan Liu, Yushun Xiang +16
Recently, with the rapid development of robot learning and imitation learning, numerous datasets and methods have emerged. However, these datasets and their task designs often lack…