Researchers report building photonic computing chips that use light pulses to train spiking neural networks on robotic-control-style benchmark tasks, aiming to shift more of the learning workload from ...

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

Researchers have built new photonic computing chips that allow neural networks to learn using ...

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 ...

Researchers in the US developed bipedal robots with a new design, the HybridLeg platform, to advance reinforcement learning. Featuring a lantern-shaped, sensorized mechanical cover, these robots can ...

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 ...

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 ...

[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 ...