Reinforcement learning (RL) for robotics is often associated with large GPU clusters, distributed infrastructure, and x86-based development environments. Training a humanoid robot with high-fidelity ...

The field of robotics is undergoing a profound transformation driven by rapid advances in artificial intelligence, particularly large language models and ...

Figure AI has developed a new humanoid robotic natural walking capability for its humanoid robots, leveraging reinforcement learning (RL) and simulation-based training. This approach enables the ...

Researchers have introduced an online model-based reinforcement learning algorithm that trains robots directly from real-world interactions, bypassing extensive simulation. The approach builds a ...

Tesla is ramping up hiring for its humanoid robot program, Optimus, including some reinforcement learning engineers. It was hard to take Tesla Bot seriously when Elon Musk announced it by having ...

Reinforcement learning is a subset of machine learning. It enables an agent to learn through the consequences of actions in a specific environment. It can be used to teach a robot new tricks, for ...

Intrinsic motivation, a concept drawn from behavioural science, has gained significant traction in robotic research as a means to stimulate exploratory behaviour in the absence of explicit external ...

[Aditya Sripada] and [Abhishek Warrier]’s TARS3D robot came from asking what it would take to make a robot with the capabilities of TARS, the robotic character from Interstellar. We couldn’t find a ...

A paddle-wielding robot is so adept at playing table tennis that it is posing a tough challenge to elite human players and ...

Sony AI's table tennis robot, Ace, has become the first autonomous system to defeat elite human players in official matches, as reported in Nature. Combining event-based vision sensors, reinforcement ...