Based Planner

Based planners are algorithms that generate sequences of actions to achieve a goal, leveraging models of the environment and robot dynamics. Current research focuses on improving efficiency and robustness in challenging scenarios, employing techniques like bi-level search for compliant motion planning, kinodynamic A* search coupled with occupancy map prediction for navigation, and hybrid approaches combining rule-based and learning-based methods (including LLMs) for enhanced adaptability. These advancements are crucial for enabling autonomous robots to perform complex tasks in dynamic and uncertain environments, with applications ranging from assembly to autonomous driving and exploration.