Deepreinforcement learning has disadvantages such as low sample utilization and slow convergence, and thousandsof trial-and-error iterations are required to perform ...

THESE DROIDS HOW TO FUNCTION. RIGHT NOW, WE ARE STEPPING BACK INTO THE FUTURE WITH A RARE LOOK INSIDE THE ROBOTICS INSTITUTE AT CMU. THE WORK BEING INVENTED RIGHT HERE IN PITTSBURGH WILL HAVE A MAJOR ...

What if robots could learn to adapt to their surroundings as effortlessly as humans do? The rise of quadruped robots, like Boston Dynamics’ Spot, is turning this vision into reality. By integrating ...

TL;DR: FigureAI has developed an AI-powered walking controller for its Figure 02 humanoid robot, enhancing its movement to be more human-like with features such as heel strikes and synchronized arm ...

The integration of deep reinforcement learning with PD control in humanoid robots enhances gait stability and patient comfort ...

AgiBot, a humanoid robotics company based in Shanghai, has engineered a way for two-armed robots to learn manufacturing tasks through human training and real-world practice on a factory production ...

Fighting fires could be done remotely without the need to place firefighting crews directly in potentially dangerous ...