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dc.contributor.authorTilbury, Dawn M.en_US
dc.date.accessioned2013-09-19T18:50:58Z
dc.date.available2013-09-19T18:50:58Z
dc.date.issued2013-09-11
dc.identifier.urihttp://hdl.handle.net/1853/49004
dc.descriptionPresented on September 11, 2013 from 12:00 pm - 1:00 pm in the TSRB Auditorium.en_US
dc.descriptionDawn M. Tilbury received a BS degree in electrical engineering, summa cum laude, from the University of Minnesota in 1989, and an MS and PhD degree in electrical engineering and computer sciences from the University of California, Berkeley, in 1992 and 1994, respectively. In 1995, she joined the faculty of the University of Michigan, Ann Arbor, where she is currently a professor of mechanical engineering with a joint appointment in Electrical Engineering and Computer Science. Tilbury’s research interests lie broadly in the area of control systems, including applications for robotics and manufacturing systems. She was program chair of ACC 2012 and will be general chair of ACC 2014. Tilbury is a life member of SWE, and Fellow of ASME and IEEE.en_US
dc.descriptionRuntime: 51:57 minutes.en_US
dc.description.abstractVehicles 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.en_US
dc.format.extent51:57 minutes
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.relation.ispartofseriesIRIM Seminar Seriesen_US
dc.subjectRoboticsen_US
dc.subjectTeleoperated mobile manipulatorsen_US
dc.subjectAutonomous machinesen_US
dc.titleCharacterizing and Improving the Performance of Teleoperated Mobile Manipulatorsen_US
dc.typeVideoen_US
dc.typeLectureen_US
dc.contributor.corporatenameUniversity of Michiganen_US


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  • IRIM Seminar Series [121]
    Each semester a core seminar series is announced featuring guest speakers from around the world and from varying backgrounds in robotics.

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