Active load damping of an extending boom crane using a low cost RGB-D camera
Department of Mechanical Engineering-Engineering Mechanics
© 2017 IEEE. A vision based tracking algorithm was developed for active load damping on a 1/9th scale extending boom crane using the Microsoft Xbox 360 Kinect RGB-D camera. The damping performance was compared to the IMU approach based on the Microstrain Inertia Link sensor. With the IMU solution, the radial damping ratio was improved by a factor of 2.2 and an order of magnitude in the tangential direction. The vision solution achieved a damping ratio improvement by a factor 2.0 and 4.7 in the radial and tangential directions respectively. The settling times for both sensors were with a few seconds at a total duration of 25 and 15 seconds for the radial and tangential directions when active damping was applied. The cranes response was a limiting factor in the system's damping performance as it would be with a full scale crane.
SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings
Active load damping of an extending boom crane using a low cost RGB-D camera.
SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings.
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