This multi-objective setup encourages natural walking behavior rather than rigid or inefficient movement. A four-stage ...

The companies have jointly developed an AI robot control system that can interact with the physical world and be used in various fields from logistics to rescue operations. Tests have shown that in ...

Last year, PNDbotics debuted its latest humanoid platforms at WAIC 2025, highlighting advances in actuation, control, and ...

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

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

Boasting a sophisticated design tailored for versatile mobility, Cassie demonstrates remarkable agility as it effortlessly navigates quarter-mile runs and performs impressive long jumps without ...

Prior deep learning experience (e.g. ELEC_ENG/COMP_ENG 395/495 Deep Learning Foundations from Scratch ) and strong familiarity with the Python programming language. Python will be used for all coding ...

Breakthroughs, discoveries, and DIY tips sent every weekday. Terms of Service and Privacy Policy. Researchers are training robots to perform an ever-growing number of ...

Boston Dynamics Wednesday announced a partnership designed to bring improved reinforcement learning to its electric Atlas humanoid robot. The tie-up is with the Robotics & AI Institute (RAI Institute) ...