“I want that”: Human-in-the-loop control of a wheelchair-mounted robotic arm

Authors:
Katherine M. Tsui;Dae-Jin Kim;Aman Behal;David Kontak;Holly A. Yanco
Affiliations:
University of Massachusetts Lowell, Lowell, MA, USA;Universal Robotics, Inc., Noshville, TN, USA and University of Central Florida, Orlando, FL, USA;University of Central Florida, Orlando, FL, USA;Crotched Mountain Rehabilitation Center, Greenfield, NH, USA;University of Massachusetts Lowell, Lowell, MA, USA
Venue:
Applied Bionics and Biomechanics - Assistive and Rehabilitation Robotics
Year:
2011

Citing 10
Cited 0

Introduction to statistical pattern recognition (2nd ed.)

Introduction to statistical pattern recognition (2nd ed.)
Three-dimensional computer vision: a geometric viewpoint

Three-dimensional computer vision: a geometric viewpoint
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

Communications of the ACM
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
Collaborative Control of the Manus Manipulator

Universal Access in the Information Society
Scalable Recognition with a Vocabulary Tree

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Development and evaluation of a flexible interface for a wheelchair mounted robotic arm

Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction
Laser pointers and a touch screen: intuitive interfaces for autonomous mobile manipulation for the motor impaired

Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility
Eye-in-hand stereo visual servoing of an assistive robot arm in unstructured environments

ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Developing heuristics for assistive robotics

Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction

Quantified Score

Hi-index	0.00

Visualization

Abstract

Wheelchair-mounted robotic arms have been commercially available for a decade. In order to operate these robotic arms, a user must have a high level of cognitive function. Our research focuses on replacing a manufacturer-provided, menu-based interface with a vision-based system while adding autonomy to reduce the cognitive load. Instead of manual task decomposition and execution, the user explicitly designates the end goal, and the system autonomously retrieves the object. In this paper, we present the complete system which can autonomously retrieve a desired object from a shelf. We also present the results of a 15-week study in which 12 participants from our target population used our system, totaling 198 trials.