Gait Optimization

Gait optimization focuses on designing and controlling the movement patterns of legged robots and other locomoting systems to maximize efficiency, stability, and adaptability across diverse terrains and conditions. Current research emphasizes developing efficient algorithms, such as evolutionary algorithms, geometric optimal control methods, and bi-level optimization schemes, often incorporating advanced model architectures like diffusion models and transformers to handle high-dimensional systems and complex constraints. These advancements are crucial for improving the performance of robots in various applications, from search and rescue to manufacturing and assistive technologies, and also contribute to a deeper understanding of biological locomotion. Furthermore, the field is actively addressing challenges in gait transition smoothness, robustness to disturbances, and accurate gait recognition from visual data.