Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning
Lucas Manuelli, Russ Tedrake(McGovern Institute for Brain Research), Pete Florence(Google (United States)), Yunzhu Li(Ministry of Education of the People's Republic of China)
Conference on Robot Learning
January 1, 2020
Cited by 16
Related Papers
Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot
|Autonomous Robots|2015|830
Towards Generalist Biomedical AI
|NEJM AI|2024|386
An Architecture for Online Affordance‐based Perception and Whole‐body Planning
|Journal of Field Robotics|2014|140