Dynamic Legged Robot

Dynamic legged robots aim to create machines capable of agile and robust locomotion across diverse terrains, mimicking the capabilities of animals. Current research heavily focuses on optimizing gait generation and control through methods like reinforcement learning, model predictive control (including differential dynamic programming and its variants), and Hamilton-Jacobi reachability analysis, often incorporating whole-body control and terrain awareness. These advancements are driven by the need for improved stability, efficiency, and adaptability in challenging environments, with applications ranging from logistics and search and rescue to assistive robotics. The development of novel metrics and model architectures, such as those incorporating compliant elements and multi-agent systems, further enhances the field's progress.