Local Planning for Unmanned Ground Vehicles using Imitation Learning
Mobile robotics is an expanding field worldwide leading to the need for advanced path-planning algorithms that can traverse various environments. Current state-ofthe- art path-planning algorithms used at the Swedish Defence Research Agency, FOI, tend to be inflexible and parameter dependent. The parameters might need to be tuned for each new environment, which is a very labor-intensive process. T