Motion Planning Problem

Motion planning, the problem of finding collision-free paths for robots or other agents, aims to generate optimal trajectories that satisfy various constraints and objectives. Current research emphasizes improving the efficiency and robustness of existing algorithms like Rapidly-exploring Random Trees (RRT) and Particle Swarm Optimization (PSO), often incorporating techniques like trajectory optimization, message passing, and data-driven methods to handle high-dimensional spaces and dynamic environments. These advancements are crucial for enabling autonomous navigation and manipulation in complex, real-world scenarios, impacting fields such as robotics, autonomous driving, and computational biology.