Deep-reinforcement-learning-based robot motion strategies for grabbing objects from human hands Peer-Reviewed Publication Beijing Zhongke Journal Publising Co. Ltd.

Task and motion planning Reinforcement learning tests have different degrees of difficulty. Most current tests involve navigation tasks, where an RL agent must find its way through a virtual ...

AI-assisted design methods now allow for automated optimization, drastically shortening development cycles while boosting ...

Researchers have taught legged robots to throw using their entire bodies, boosting power and accuracy in object launching.

Researchers have developed an Artificial Intelligence (AI) system that enables a four-legged robot to adapt its gait to ...

Reinforcement learning techniques could be the keys to integrating robots — who use machine learning to output more than words — into the real world.

Kaibo He is a research scientist at Clone Robotics, where he specialises in reinforcement learning and motion control.His pioneering work centres on developing algorithms to drive high-dimensional ...

At each time step, TAMER chooses the action that is predicted to directly elicit the most reward, eschewing consideration of the action’s effect on future state (i.e., in reinforcement learning ...