Uneven Terrain

Research on uneven terrain focuses on enabling robots and vehicles to navigate and operate effectively in unstructured environments, addressing challenges in stability, safety, and energy efficiency. Current efforts leverage various machine learning approaches, including deep reinforcement learning, Gaussian processes, and neural networks, often integrated with model predictive control or other optimization techniques to generate robust and efficient trajectories. This research is crucial for advancing autonomous navigation in diverse applications, from autonomous vehicles and prosthetics to legged robots exploring challenging terrains, impacting fields like robotics, transportation, and assistive technologies.