Abstract
Abstract The payload oscillation inherent to all cranes makes it challenging for human operators to manipulate payloads quickly, accurately, and safely. An input-shaping controller was implemented on a large bridge crane at the Georgia Institute of Technology to reduce crane payload oscillation. The crane was used to study the performance of human operators as they drove the crane through obstacle courses. An image processing system was implemented to track the movement of the crane payload. Data from these experiments show that operators performed manipulation tasks faster, safer, and more effectively when input shaping was utilized to reduce payload sway.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Dynamic Systems, Measurement, and Control
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
