Diffusion-Based Global Path Planning

Path planning is the difference between a robot that “knows where to go” and one that just reacts locally. For legged robots in cluttered indoor spaces (inspection, warehouses, disaster response), planning needs to be fast, reliable, and robust to weird map layouts. The project tackles this by reframing global planning as a generative modeling problem: instead of searching, it generates a whole path in iterative denoising via denoising diffusion conditioned on a map image.