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Assistive Teleoperation of Robot Arms via Automatic Time-Optimal Mode Switching.
Laura V Herlant1, Rachel M Holladay1, Siddhartha S Srinivasa1
1The Robotics Institute, Carnegie Mellon University.
Proceedings of the ... ACM SIGCHI. ACM Conference on Human-Robot Interaction
|July 24, 2018
Summary
Mode switching for assistive robotic arms is time-consuming and cognitively demanding for users with disabilities. Automating mode switching significantly enhances user satisfaction and reduces control time.
Area of Science:
- Robotics
- Human-Computer Interaction
- Rehabilitation Engineering
Background:
- Assistive robotic arms empower individuals with upper extremity disabilities to perform daily activities.
- Controlling high-dimensional robotic arms with low-dimensional interfaces (e.g., joysticks) often requires mode switching.
- Mode switching presents significant time and cognitive challenges for users, hindering effective control.
Purpose of the Study:
- To investigate the challenges associated with mode switching in assistive robotic arm control.
- To evaluate the impact of automated mode switching on user experience and control efficiency.
- To identify potential improvements for human-robot interaction in assistive robotics.
Main Methods:
- User interviews with daily users of the Kinova JACO arm to identify control challenges.
- Objective measurement of time consumed by mode switching during robotic arm operation.
- Implementation and evaluation of an automated mode switching intervention based on a time-optimality model.
Main Results:
- Mode switching was identified as a major usability issue by daily users.
- Mode switching accounted for approximately 17.4% of the total task execution time.
- Automated mode switching, even with a simple model, led to significant improvements in user satisfaction.
Conclusions:
- Mode switching is a critical bottleneck in current assistive robotic arm control systems.
- Automating mode switching can substantially improve user satisfaction and reduce task completion time.
- Further research into intelligent control strategies can enhance the usability of assistive robotic arms.
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