ARC-LfD: Using Augmented Reality for Interactive Long-Term Robot Skill Maintenance via Constrained Learning from Demonstration
Matthew B. Luebbers Connor Brooks Carl L. Mueller Daniel Szafir Bradley Hayes Matthew B. Luebbers Connor Brooks Carl L. Mueller Daniel Szafir Bradley Hayes
Learning from Demonstration (LfD) enables novice users to teach robots new skills. However, many LfD methods do not facilitate skill maintenance and adaptation. Changes in task requirements or in the environment often reveal the lack of resiliency and adaptability in the skill model. To overcome these limitations, we introduce ARC-LfD: an Augmented Reality (AR) interface for constrained Learning f...