Semi-autonomous unmanned aerial manipulator teleoperation for push-and-slide inspection using parallel force/vision control

Abstract

Performing inspection and maintenance tasks with aerial robots in complex industrial facilities require high levels of maneuverability and dexterity. As full autonomy still struggles to provide robust solutions due to limited adaptability and high development costs, this study explores the paradigm shift towards shared control teleoperation for tilting unmanned aerial manipulators (UAMs). The research initially focuses on integrating onboard camera measurements and interaction force feedback within a parallel force/vision controller for push–and–slide inspection tasks. The control loop lends itself to the development of a semi-autonomous operation architecture that enables a human operator to easily accomplish the task by means of a simple input device. The paper presents a user study evaluating task completion performance with human–in–the–loop control versus fully autonomous execution. Statistical analysis of 20 user experiences provides insights into the levels of autonomy necessary for effective task completion. Among the analyzed control modalities, statistically significant differences arise when the sliding feature is autonomous, denoting it as the most difficult to manually accomplish. The investigation is conducted within a simulated environment to ensure the safety of sensitive instruments and accommodate users with varying levels of expertise. By proposing shared control architectures, this research addresses the challenges of autonomous UAM operations in hazardous industrial environments, highlighting the benefits of human oversight and control in enhancing task efficiency and safety. • Push-and-slide Non-destructive Tests require safe movements and high dexterity. • Novel parallel force/vision control of aerial manipulator for physical inspection. • Semi-autonomous control paradigm including a human guided haptic device. • Human subject statistical analysis study evaluating the right level of semi-autonomy needed for task completion. • Simulation based result developing a training environment for different users to learn how to drive UAM to complete inspection tasks.