3 papers
cs.RO2026
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…
cs.RO2026
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…
cs.RO2025
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…