Abstract
During robot teaching and physical human-robot interaction (pHRI), external forces and torques are required to be measured. However, the gravity acted on collaborative tools is a known-structure but unknown parameters input for pHRI systems. It is an essential process that gravity parameters need to be estimated and compensated using six-dimension force sensor calibration in a pHRI linear system based on Newton-Euler (NE) equation. In the previous work, the collaborative robot (cbot) system interacting with human and environment has 2 orthogonal installation six-dimension force sensors, where sensors' biasing and static wrenches exist. To solve this problem for both six-dimension force sensors in the same time, a regression algorithm in 3 steps is proposed using ridge regression and least square regression.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
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.