Video: Humanoid robot goes 'mountain-grade' while picking up litter

Flexion Robotics has released a demonstration video showcasing its humanoid robot equipped with a new autonomy framework that enables it to navigate challenging outdoor terrain and perform litter cleanup tasks independently, without prior training. The robot identifies scattered objects, picks them up, and deposits them into a trash bin, highlighting advances in real-world robotic autonomy. The company’s technology integrates reinforcement learning and sim-to-real transfer to train low-level motor skills in simulation, which are then executed reliably on physical robots. This approach addresses the scalability challenge of collecting real-world data for every possible scenario by combining core learned skills with high-level decision-making powered by large language and vision-language models. The system is structured as a three-layer modular hierarchy: at the top, a language or vision-language model handles task planning, common-sense reasoning, and breaking down goals into actionable steps; the middle layer generates safe, short-range motions based on perception and instructions; and the base layer uses reinforcement learning controllers to execute these motions robustly across different environments and robot