Recently, several works achieve end-to-end visual servoing (VS) for robotic manipulation by
replacing traditional controller with differentiable neural networks, but lose the ability to …

Reinforcement learning (RL) for robot control typically requires a detailed representation of
the environment state, including information about task-relevant objects not directly …

This study explores a learning-based tri-finger robotic arm manipulating task, which requires
complex movements and coordination among the fingers. By employing reinforcement …

Robotic grasping poses a fundamental challenge in robotics, particularly when dealing with
unknown objects. This skill has always been a focal point in robotics research due to its …

Reinforcement learning, as an effective framework for solving continuous decision tasks in
machine learning, has been widely used in manipulator decision control. However, for …