Crane trained with AI technology performs automated point-to-point operation while suppressing the load sway.
DeepX, Inc. and Tadano Ltd. have released the progress of a joint research project of crane automation utilizing AI technology.
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Background and purpose of this project
Cranes are general-purpose lifting equipment widely used in construction industries. Crane operators must operate multiple levers simultaneously while checking the position of the load visually. In addition, cranes are affected by the boom deflection and wind, so it takes a long time to become a proficient crane operator. On the other hand, the number of skilled crane operators in Japan is declining due to the aging population. The aim of this joint R&D project is to improve safety at work sites by simplifying and automating mobile crane operations by utilizing AI technologies.
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Crane automation and its technical approach
Mobile cranes are known to be one of the most difficult machines to operate on construction sites. Slewing and elevating motion in mobile cranes typically generates undesirable two-dimensional load-sway; therefore, crane operators must be highly skilled to suppress this sway upon completion of the point-to-point crane maneuver. DeepX and Tadano have therefore developed a control algorithm based on AI technology, levaredging simulator environment for controller optimization. Using this algorithm, the operator can safely and accurately move the load to the desired position while suppressing load sway.
Future prospects
DeepX will continue to work with Tadano to challenge more complex operations and further advance the technology for mobile crane automation. DeepX will also aim to apply this technology to various types of cranes in a wide range of industries.
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