Global Path Planning

Global path planning aims to find optimal collision-free routes for robots and autonomous vehicles, often in complex and dynamic environments. Current research emphasizes efficient algorithms, such as those based on wavefront propagation, A*, RRT*, and reinforcement learning, with a growing focus on incorporating social awareness and handling uncertainties in dynamic settings through techniques like visibility graphs and continuous curvature integration. These advancements are crucial for improving the safety, efficiency, and robustness of autonomous systems in diverse applications, from warehouse logistics and search-and-rescue operations to autonomous driving and assistive robotics.