Trajectory Optimization

Trajectory optimization focuses on finding the best possible path for a system, whether a robot, vehicle, or even a simulated process like image restoration, by minimizing a cost function subject to constraints. Current research emphasizes integrating advanced models like diffusion models and neural networks with classical optimization techniques, often employing methods such as Model Predictive Control (MPC), A* search, and various gradient-based approaches to handle complex dynamics and constraints. This field is crucial for advancing robotics, autonomous systems, and other areas requiring efficient and safe path planning, with applications ranging from autonomous driving and manipulation to manufacturing and space exploration.