4 papers
INTACT: Isomorphic Intent-to-Action Learning for Search-Free World Models
Junhan Sun, Hao Zhao, Guofeng Zhang
Forward latent world models predict how actions change a scene, but recover actions for a desired change only through expensive test-time search. We introduce INTACT (INtent-To-ACT…
LAMP: Lift Image-Editing as General 3D Priors for Open-world Manipulation
Jingjing Wang, Zhengdong Hong, Chong Bao +3
Human-like generalization in open-world remains a fundamental challenge for robotic manipulation. Existing learning-based methods, including reinforcement learning, imitation learn…
Force-Aware Residual DAgger via Trajectory Editing for Precision Insertion with Impedance Control
Yiou Huang, Ning Ma, Weichu Zhao +4
Imitation learning (IL) has shown strong potential for contact-rich precision insertion tasks. However, its practical deployment is often hindered by covariate shift and the need f…
PALo: Learning Posture-Aware Locomotion for Quadruped Robots
Xiangyu Miao, Jun Sun, Hang Lai +4
With the rapid development of embodied intelligence, locomotion control of quadruped robots on complex terrains has become a research hotspot. Unlike traditional locomotion control…