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Predictive Graphical User Interface Elements to Improve Crane Operator Performance

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4 Author(s)
Joshua Vaughan ; Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA ; Anderson Smith ; Se Joong Kang ; William Singhose

Operating cranes is challenging because the payload significantly lags behind the control input and can undergo large amplitude oscillations. While significant work has been directed at reducing the payload swing, little effort has been placed on reducing the time lag. There is a good reason for neglecting the time lag; it cannot be eliminated. It is a result of the physical limitations of the crane; motor torque limits coupled with the very large inertia of cranes and their payloads cause sluggish behavior. Experienced crane operators become accustomed to the time lag and develop the skill to start decelerating the crane well before the desired stopping location. This paper presents a control method that aids the human operator by graphically displaying a prediction of where the crane will stop. This predictive element is combined with an input-shaping controller that both reduces the payload swing and simplifies the implementation of the predictive element. Results from a study of crane operators show that the proposed control system significantly improves tower crane performance, in terms of both task completion time and positioning accuracy.

Published in:

IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans  (Volume:41 ,  Issue: 2 )