Advances on Affordable Hardware Platforms for Human Demonstration Acquisition in Agricultural Applications

This paper presents advances on the Universal Manipulation Interface (UMI) , a low-cost hand-held gripper for robot Learning from Demonstration (LfD), for complex in-the-wild scenarios found in agri- cultural settings. The focus is on improving the acquisition of suitable samples with minimal additional setup. Firstly, idle times and user’s cog- nitive load are reduced through the extraction of individual samples from a continuous demonstration considering task events. Secondly, reliability on the generation of task sample’s trajectories is increased through the combination on-board inertial measurements and external visual marker localization usage using Extended Kalman Filtering (EKF). Results are presented for a fruit harvesting task, outperforming the default pipeline.