Robust Walking

Robust walking in robots aims to create locomotion strategies that are stable and adaptable across diverse and unpredictable terrains. Current research focuses on developing controllers, often using reinforcement learning or discrete-time barrier functions, that enable robots (both bipedal and quadrupedal) to maintain balance and navigate obstacles with minimal reliance on precise environmental sensing. These advancements are significant for improving the reliability and versatility of robots in real-world applications, such as search and rescue, exploration, and assistive technologies, and also offer insights into the principles of human locomotion.