Optimal Trajectory Generation

Optimal trajectory generation focuses on finding the best path for a robot or vehicle to follow, minimizing time, energy, or other costs while adhering to constraints like dynamics, obstacles, and safety. Current research emphasizes diverse approaches including model predictive control, reinforcement learning, and diffusion-based optimization, often tailored to specific applications such as autonomous drone racing, human-robot collaboration, and aerial surveying. These advancements improve efficiency, safety, and adaptability in various robotic and autonomous systems, impacting fields from manufacturing and logistics to search and rescue operations.