Enhanced RRT

Enhanced Rapidly-exploring Random Trees (RRTs) aim to improve the efficiency and robustness of this popular motion planning algorithm, primarily by addressing limitations in handling complex dynamics, uncertainties, and high-dimensional spaces. Current research focuses on incorporating advanced steering mechanisms, integrating control barrier functions and neural networks for safer and more efficient exploration, and developing risk-aware variants for uncertain environments. These advancements are significant for robotics, enabling more reliable and efficient autonomous navigation in challenging real-world scenarios, such as cluttered spaces and dynamic environments.