This paper discusses the grasp force sensing capabilities of the fingernail imaging method integrated with a visual servoing robotic system. The effectiveness of the fingernail imaging method has been demonstrated on the previous works in the prediction of 3-D fingertip forces. In this study, the fingernail imaging method has been modified to be used in constrained grasping studies. Moreover, the technique can be extended to be applied to the unconstrained grasping study as well. Visual servoing has been utilized in this paper to solve the issue of keeping fingernail images in the field of view of the camera during unconstrained grasping motions. The experimental results show the effectiveness of applying visual servoing for use with the fingernail imaging method to be used in grasping studies. Experimental studies were performed on 2 human subjects and the mean value of RMS errors for predicted normal forces during grasping has been found as 0.57 N. (5.7% for the range of 0–10 N)
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ASME 2018 Dynamic Systems and Control Conference
September 30–October 3, 2018
Atlanta, Georgia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5189-0
PROCEEDINGS PAPER
Grasp Force Sensing Using Visual Servoing and Fingernail Imaging
Navid Fallahinia,
Navid Fallahinia
University of Utah, Salt Lake City, UT
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Sonoma Harris,
Sonoma Harris
University of Utah, Salt Lake City, UT
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Stephen Mascaro
Stephen Mascaro
University of Utah, Salt Lake City, UT
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Navid Fallahinia
University of Utah, Salt Lake City, UT
Sonoma Harris
University of Utah, Salt Lake City, UT
Stephen Mascaro
University of Utah, Salt Lake City, UT
Paper No:
DSCC2018-9097, V001T04A010; 10 pages
Published Online:
November 12, 2018
Citation
Fallahinia, N, Harris, S, & Mascaro, S. "Grasp Force Sensing Using Visual Servoing and Fingernail Imaging." Proceedings of the ASME 2018 Dynamic Systems and Control Conference. Volume 1: Advances in Control Design Methods; Advances in Nonlinear Control; Advances in Robotics; Assistive and Rehabilitation Robotics; Automotive Dynamics and Emerging Powertrain Technologies; Automotive Systems; Bio Engineering Applications; Bio-Mechatronics and Physical Human Robot Interaction; Biomedical and Neural Systems; Biomedical and Neural Systems Modeling, Diagnostics, and Healthcare. Atlanta, Georgia, USA. September 30–October 3, 2018. V001T04A010. ASME. https://doi.org/10.1115/DSCC2018-9097
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