Local Trajectory

Local trajectory planning focuses on generating safe and efficient paths for robots and autonomous vehicles in dynamic environments, addressing immediate obstacle avoidance and adherence to constraints like traffic rules. Current research emphasizes robust methods that handle uncertainty, such as probabilistic models and deep reinforcement learning integrated with classical planners like Hybrid A* and Pure Pursuit, often incorporating risk assessment and control barrier functions for safety. These advancements are crucial for improving the reliability and performance of autonomous systems in various applications, from robotics and autonomous driving to swarm robotics and non-prehensile manipulation.