Carnegie Mellon University
Assistive Teleoperation of Robot Arms via Automatic Time-Optimal Mode Switching

Laura Herlant, Rachel Holladay , and Siddhartha Srinivasa
Human-Robot Interaction, March, 2016.

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Assistive robotic arms are increasingly enabling users with upper extremity disabilities to perform activities of daily living on their own. However, the increased capability and dexterity of the arms also makes them harder to control with simple, low-dimensional interfaces like joysticks and sip-and-puff interfaces. A common technique to control a high-dimensional system like an arm with a low-dimensional input like a joystick is through switching between multiple control modes. However, our interviews with daily users of the Kinova JACO arm identified mode switching as a key problem, both in terms of time and cognitive load. We further confirmed objectively that mode switching consumes about 17.4% of execution time even for able-bodied users controlling the JACO. Our key insight is that using even a simple model of mode switching, like time optimality, and a simple intervention, like automatically switching modes, significantly improves user satisfaction.

human-robot collaboration, assistive teleoperation, mode switching, robotic arms, time optimality

Associated Center(s) / Consortia: Quality of Life Technology Center, National Robotics Engineering Center, and Center for the Foundations of Robotics
Associated Lab(s) / Group(s): Personal Robotics
Number of pages: 8

Text Reference
Laura Herlant, Rachel Holladay , and Siddhartha Srinivasa, "Assistive Teleoperation of Robot Arms via Automatic Time-Optimal Mode Switching," Human-Robot Interaction, March, 2016.

BibTeX Reference
   author = "Laura Herlant and Rachel {Holladay } and Siddhartha Srinivasa",
   title = "Assistive Teleoperation of Robot Arms via Automatic Time-Optimal Mode Switching",
   booktitle = "Human-Robot Interaction",
   month = "March",
   year = "2016",