Learning Robust Autonomous Navigation and Locomotion for Wheeled-Legged Robots This autonomous navigation system, developed for Robotic Systems Lab's wheeled-legged quadrupeds, is designed for efficient navigation in large urban environments. Using neural network policies, the unified control system supports smooth gait transitions, intelligent navigation planning, and responsive obstacle avoidance in urban settings. Video source: Robotic Systems Lab: Legged Robotics at ETH Zürich #robotics #tec

For robots to successfully locomote in different environments, it is better to equip them with multiple modes of locomotion. Multimodal locomotion for existing robotic systems is generally realized by integrating multiple mechanisms into a single robot. These robots are generally cumbersome or challenging to control and actuate. Recently, shape-morphing structures are utilized to enable reconfigurable and multifunctional robots. In this article, the authors present a novel origami-inspired modul

Reinforcement learning has proven to aid locomotion control of highly articulated robotic systems. | Interesting Engineering

ROS Developers LIVE CLASS #68: How to Control 2 Arm Robots with Moveit

Learning Robust Autonomous Navigation and Locomotion for Wheeled-Legged Robots This autonomous navigation system, developed for Robotic Systems Lab's wheeled-legged quadrupeds, is designed for efficient navigation in large urban environments. Using neural network policies, the unified control system supports smooth gait transitions, intelligent navigation planning, and responsive obstacle avoidance in urban settings. Video source: Robotic Systems Lab: Legged Robotics at ETH Zürich #robotics #tec