Simple Near-Realtime Crane Workspace Mapping Using Machine Vision

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.