Hierarchical Navigation

Hierarchical navigation focuses on enabling agents, robots, or virtual characters to efficiently navigate complex environments by breaking down the task into smaller, manageable sub-goals. Current research emphasizes robust methods for handling uncertainty and dynamic obstacles, often employing hierarchical planning architectures that combine high-level strategic planning with low-level reactive control, incorporating techniques like dynamic gap analysis and trajectory optimization. These advancements are crucial for improving the safety and efficiency of autonomous systems in diverse settings, ranging from crowded urban spaces to virtual worlds, and have significant implications for robotics, AI, and virtual reality applications.