Researchers at the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory and the University of Texas at Austin have developed an algorithm that could have big implications for autonomous vehicles. With the algorithm, autonomous ground vehicles are able to improve their own navigation systems by watching a human drive.
The approach developed by the researchers is called adaptive planner parameter learning from demonstration, or APPLD. It was tested on an Army experimental autonomous ground vehicle.
The research was published in IEEE Robotics and Automation Letters. The work is titled “APPLD: Adaptive Planner Parameter Learning From Demonstration.”