Robot Path Planning

Robot path planning focuses on efficiently and safely guiding robots through environments, often cluttered with obstacles, while considering factors like energy efficiency, privacy, and time constraints. Current research emphasizes integrating advanced algorithms like A*, RRT*, and reinforcement learning (including DQN variants) with other techniques such as large language models and probabilistic methods to improve path optimization, robustness, and adaptability to dynamic environments. These advancements are crucial for enabling autonomous navigation in complex scenarios, impacting fields ranging from warehouse automation and manufacturing to assistive robotics and exploration.