Funnel planning and control for manipulators using neural Signed Configuration Distance Functions
This work proposes a novel funnel planning and control solution that uses a neural Signed Configuration Distance Function (nSCDF) to estimate collision-free balls and gradients in a computationally efficient way and observes improved motion performance and robustness properties when using the nSCDF for funnel control.