  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.
