2 papers
cs.RO2026
Efficient Real-World Online Reinforcement Learning for Robot Manipulation via Centralized Training and Critic Decomposition
Changhao Li, Yifang Zhang, Heng Zhang +6
Real-world online reinforcement learning (RL) provides a promising approach for training robotic manipulation policies directly in the physical world, avoiding the sim-to-real gap…
cs.RO2025
A High-Force Gripper with Embedded Multimodal Sensing for Powerful and Perception Driven Grasping
Edoardo Del Bianco, Davide Torielli, Federico Rollo +6
Modern humanoid robots have shown their promising potential for executing various tasks involving the grasping and manipulation of objects using their end-effectors. Nevertheless,…