Characterizing and Improving the Performance of Teleoperated Mobile Manipulators

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Tilbury, Dawn M.
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Vehicles in racing simulation video games speed down virtual racecourses in excess of 100mph. However, teleoperated mobile manipulators in search and rescue operations inch along at an excruciatingly slow pace, even though time is of the essence. In both cases, the human operator is in the loop, giving control input to the vehicle. In the first case, however, the driver only needs to control the direction of the vehicle through a steering wheel or joystick; in the second case, the additional degrees of freedom of the manipulator arm are added. Of course, the environments are also different: a structured simulated world as opposed to a uncertain real disaster area. For multiple reasons including communications latency, actuator limitations, and inefficient human-robot interaction strategies, even basic robot teleoperation tasks are excruciatingly slow, both in robot mobility and manipulator arm control. For robots to become more useful tools for humans in the future, the speed at which robotassisted tasks can be completed must be increased. In this talk, I present a framework we have developed for characterizing and understanding the key factors that limit the performance of teleoperated mobile manipulators, where performance is defined as a combination of speed, accuracy and safety (lack of collisions). Our analysis framework depends on a having models of delay and performance for the different components of the system, and I describe some models that we have created based on user testing. We consider operator feedback using video and virtual reality, and compare a gamepad user input to a master-slave manipulator. Since adding semi-autonomous behaviors to a teleoperated robot can improve the performance, we describe our results in rollover prevention. I conclude with a discussion of future work in the area.
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51:57 minutes
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