4 papers · 1 filter
3D Point World Models: Point Completion Enables More Accurate Dynamics Learning
Skand Peri, Hung Nguyen, Chanho Kim +2
Learning predictive models of the world enables robotic control through planning, potentially allowing robots to improvise solutions on new tasks. However, large video-based dynami…
Learning Hybrid-Control Policies for High-Precision In-Contact Manipulation Under Uncertainty
Hunter L. Brown, Geoffrey Hollinger, Stefan Lee
Reinforcement learning-based control policies have been frequently demonstrated to be more effective than analytical techniques for many manipulation tasks. Commonly, these methods…
Non-conflicting Energy Minimization in Reinforcement Learning based Robot Control
Skand Peri, Akhil Perincherry, Bikram Pandit +1
Efficient robot control often requires balancing task performance with energy expenditure. A common approach in reinforcement learning (RL) is to penalize energy use directly as pa…
Point Cloud Models Improve Visual Robustness in Robotic Learners
Skand Peri, Iain Lee, Chanho Kim +3
Visual control policies can encounter significant performance degradation when visual conditions like lighting or camera position differ from those seen during training -- often ex…