Collision-free Path Planning in the Latent Space through cGANs
This addresses path planning for robots, but it appears incremental as it builds on existing cGAN and planning methods.
The paper tackles collision-free path planning for robots by using conditional GANs to map the latent space exclusively to collision-free joint configurations, enabling any planner to generate suitable paths; they verified the method with a simulated two-link robot arm.
We show a new method for collision-free path planning by cGANs by mapping its latent space to only the collision-free areas of the robot joint space. Our method simply provides this collision-free latent space after which any planner, using any optimization conditions, can be used to generate the most suitable paths on the fly. We successfully verified this method with a simulated two-link robot arm.