Using Augmented Reality to Assess and Modify Mobile Manipulator Surface Repair Plans (2311.00988v1)

Abstract: Industrial robotics are redefining inspection and maintenance routines across multiple sectors, enhancing safety, efficiency, and environmental sustainability. In outdoor industrial facilities, it is crucial to inspect and repair complex surfaces affected by corrosion. To address this challenge, mobile manipulators have been developed to navigate these facilities, identify corroded areas, and apply protective coatings. However, given that this technology is still in its infancy and the consequences of improperly coating essential equipment can be significant, human oversight is necessary to review the robot's corrosion identification and repair plan. We present a practical and scalable Augmented Reality (AR)-based system designed to empower non-experts to visualize, modify, and approve robot-generated surface corrosion repair plans in real-time. Built upon an AR-based human-robot interaction framework, Augmented Robot Environment (AugRE), we developed a comprehensive AR application module called Situational Task Accept and Repair (STAR). STAR allows users to examine identified corrosion images, point cloud data, and robot navigation objectives overlaid on the physical environment within these industrial environments. Users are able to additionally make adjustments to the robot repair plan in real-time using interactive holographic volumes, excluding critical nearby equipment that might be at risk of coating overspray. We demonstrate the entire system using a Microsoft HoloLens 2 and a dual-arm mobile manipulator. Our future research will focus on evaluating user experience, system robustness, and real-world validation.