Abstract
A system is presented for the simultaneous estimation of surface and motion parameters of a free-flying object in a telerobotics experiment. The system consists of two main components, a vision-based invariant-surface and motion estimator, and a Kalman filter. An algorithm for invariant surface and motion estimation from sparse multi-sensor range data is presented. Motion estimates from the vision module are input to a Kalman filter (KF) for tracking a 'free-flying' object in space. The predicted motion parameters from the KF are fed back to the vision module and serve as an initial guess in the search for optimal motion. >
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.
