Real Time Trajectory Planning

Real-time trajectory planning focuses on generating safe and efficient paths for robots and autonomous vehicles in dynamic environments, aiming to achieve seamless interaction with humans and other agents. Current research emphasizes methods like model predictive control (MPC), hierarchical planning approaches combining sampling-based and reactive techniques, and the use of neural networks for implicit safety constraints and reachability analysis. These advancements are crucial for enabling safe and reliable operation of robots in diverse applications, from collaborative robotics and urban air mobility to autonomous driving and aerial perching.