TY - GEN
T1 - Simple near-realtime crane workspace mapping using machine vision
AU - Rahman, M. Sazzad
AU - Vaughan, Joshua
N1 - Publisher Copyright:
© 2014 by ASME.
PY - 2014
Y1 - 2014
N2 - Overhead cranes are widely used in industries all over the world. It is not easy to move crane payloads without oscillation, increasing the likelihood of obstacle collisions and other accidents. Even experienced crane operators make mistakes that cause loss of money and time. Some reasons for these incidents are limitations of the operator's field of view, depth perception, knowledge of the workspace, and the dynamic environment of the workspace. One possible solution to these problems could be aiding the operator with a dynamic map of the workspace that shows the current position of obstacles. The probable areas of finding obstacles based on the previous positions of obstacles could also be shown. This paper describes a simple method of generating such a map of the crane workspace using machine vision.
AB - Overhead cranes are widely used in industries all over the world. It is not easy to move crane payloads without oscillation, increasing the likelihood of obstacle collisions and other accidents. Even experienced crane operators make mistakes that cause loss of money and time. Some reasons for these incidents are limitations of the operator's field of view, depth perception, knowledge of the workspace, and the dynamic environment of the workspace. One possible solution to these problems could be aiding the operator with a dynamic map of the workspace that shows the current position of obstacles. The probable areas of finding obstacles based on the previous positions of obstacles could also be shown. This paper describes a simple method of generating such a map of the crane workspace using machine vision.
UR - http://www.scopus.com/inward/record.url?scp=84929240462&partnerID=8YFLogxK
U2 - 10.1115/DSCC2014-6342
DO - 10.1115/DSCC2014-6342
M3 - Conference contribution
AN - SCOPUS:84929240462
T3 - ASME 2014 Dynamic Systems and Control Conference, DSCC 2014
BT - Industrial Applications; Modeling for Oil and Gas, Control and Validation, Estimation, and Control of Automotive Systems; Multi-Agent and Networked Systems; Control System Design; Physical Human-Robot Interaction; Rehabilitation Robotics; Sensing and Actuation for Control; Biomedical Systems; Time Delay Systems and Stability; Unmanned Ground and Surface Robotics; Vehicle Motion Controls; Vibration Analysis and Isolation; Vibration and Control for Energy Harvesting; Wind Energy
PB - American Society of Mechanical Engineers
T2 - ASME 2014 Dynamic Systems and Control Conference, DSCC 2014
Y2 - 22 October 2014 through 24 October 2014
ER -