Optimal Path Planning
Optimal path planning focuses on finding the best route between two points, considering factors like distance, obstacles, energy consumption, and time constraints. Current research emphasizes developing efficient algorithms, such as those based on wavefront propagation, reinforcement learning, and sampling-based methods like RRT*, often incorporating advanced techniques like neural networks for improved accuracy and speed, particularly in complex or dynamic environments. These advancements have significant implications for various fields, including robotics, autonomous navigation, and multi-agent systems, enabling more efficient and robust operation in diverse applications.
Papers
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