Abstract
The accuracy of robot dynamic models plays an important role in the design of stable and robust robot controllers. The accuracy of these dynamic models is largely dependent on the precise measurement of robot dynamic parameters (e.g first moments, radius of gyration matrix, etc.). Towards this end, algorithms for the identification of these parameters need to be developed to obtain dynamic models with high fidelity, which will ultimately improve the future designs of robot controllers. This work aims to provide a viable solution to this problem. A simplified model of the dynamics is used to extract and group the dynamic parameters of a robot manipulator. The resulting equations are mapped onto a network of parallel processors to speed up the rate of computations and enable real-time implementations. The efficiency of the algorithm is demonstrated by a case study.
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 callDisclaimer: 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.
