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Proceedings Paper

Control of lift assist devices for performance enhancement
Author(s): Greg R. Luecke; Kok-Leong Tan; Sean Mahrt
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Paper Abstract

Handling heavy and bulky loads in manufacturing settings is an ongoing problem in achieving flexible and re-configurable assembly operations. One current trend is toward using powered heavy lift assist devices to augment human decision making skills with the mechanical muscle necessary to move and position large work pieces. As advanced automation has made it possible to apply power to multiple axes of a lift assist device, a need has arisen to implement a more natural control interface for the operator. One method is to use sensors to measure the force applied by the operator as the motion command to the powered assist device. This approach allows an untrained operator to easily guide the work piece using natural hand motions. In this research, we explore the use of multiple powered axes in a lift assist device to enhance and increase the material handling capability of the human operator. Input forces from the operator are measured and translated into joint actuation commands using a micro-controller. The automated control system is used to augment the workspace of to include virtual walls and attraction locations that can guide the operator as the work piece is moved. Closed loop control issues arise from the three coupled, nonlinear systems meeting at the manipulator input handle--the human, the powered lift assist device, and the digital computer control application. We present analytic and experimental comparisons of the performance of this class of human strength enhancing devices. Stability of the various control approaches is considered from a theoretical standpoint and compared to experimental results. The combination of theory and experiment are used to provide boundaries to the allowable performance of these types of machines.

Paper Details

Date Published: 2 March 2001
PDF: 12 pages
Proc. SPIE 4195, Mobile Robots XV and Telemanipulator and Telepresence Technologies VII, (2 March 2001); doi: 10.1117/12.417309
Show Author Affiliations
Greg R. Luecke, Iowa State Univ. (United States)
Kok-Leong Tan, Iowa State Univ. (United States)
Sean Mahrt, Iowa State Univ. (United States)


Published in SPIE Proceedings Vol. 4195:
Mobile Robots XV and Telemanipulator and Telepresence Technologies VII
Matthew R. Stein; Howie M. Choset; Douglas W. Gage; Matthew R. Stein, Editor(s)

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