Multi-robot path planning and coordination is an interdisciplinary field that aims to develop robust algorithms enabling multiple robots to navigate complex, dynamic environments efficiently and ...

A new two-stage AI system combines physics-driven trajectory planning with adaptive reinforcement learning, enabling robots to walk smoothly, remain upright in the face of shocks, and navigate ...

Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...

ChatGPT and other AI tools are upending our digital lives, but our AI interactions are about to get physical. Humanoid robots trained with a particular type of AI to sense and react to their world ...

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 ...

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) ...

Since the early decades of artificial intelligence, humanoid robots have been a staple of sci-fi books, movies, and cartoons. Yet, after decades of research and development in AI, we still have ...

Trends such as industry-specific AI and a new data economy will affect physical AI in 2026, says a Universal Robots executive ...