Planning Pipeline

Planning pipelines aim to generate optimal sequences of actions for autonomous systems, encompassing diverse applications from robot manipulation and autonomous driving to aerial tracking and agricultural robotics. Current research emphasizes efficient and robust planning algorithms, often integrating machine learning models (like neural networks and Gaussian Processes) with classical optimization techniques (e.g., quadratic programming, linear programming, particle swarm optimization) to handle complex, high-dimensional environments and uncertainties. These advancements are crucial for improving the safety, efficiency, and adaptability of autonomous systems across various domains, impacting fields ranging from manufacturing and logistics to healthcare and exploration.