Improving UGV teleoperation performance using novel visualization techniques and manual interfaces

Abstract

Unmanned ground vehicles (UGVs) are well-suited to a variety of tasks that are dangerous or repetitive for humans to perform. Despite recent advances, UGVs still suffer from reliability issues, and human operation failures have been identified as one root cause of UGV system failure. However, most literature relevant to UGV reliability does not address the effects of human errors or the user interface. Our previous work investigated the issue of user situational awareness and sense of presence in the robot workspace by implementing a Mixed Reality interface featuring a first-person video feed with an Augmented Reality overlay and a third-person Virtual Reality display. The interface was evaluated in a series of user tests in which users manually controlled a UGV with a manipulator arm using traditional input modalities including a computer mouse, keyboard and gamepad. In this study, we learned that users found it challenging to mentally map commands from the manual inputs to the robot arm behavior. Also, switching between control modalities seemed to add to the cognitive load during teleoperation tasks. A master-slave style manual controller can provide an intuitive one-to-one mapping from user input to robot pose, and has the potential to improve both operator situational awareness for teleoperation tasks and decrease mission completion time. This paper describes the design and implementation of a teleoperated UGV with a Mixed Reality visualization interface and a master-slave controller that is suitable for teleoperated mobile manipulation tasks.