This paper presents an algorithm for the forward kinematics and online self-calibration of cable-driven parallel robots. Covariance-based metrics known as the position dilution of precision (PDOP) and orientation dilution of precision (ODOP) are introduced as a means to quantify the quality of data collected with regards to self-calibration. These metrics enable systematic pruning of the data used for self-calibration and an assessment of when sufficiently rich data has been collected to perform self-calibration. The proposed algorithm is demonstrated through inverse-kinematics- and dynamics-based numerical simulations.
Forward Kinematics and Online Self-calibration of Cable-Driven Parallel Robots with Covariance-Based Data Quality Assessment
Mechan. Machine Science
International Conference on Cable-Driven Parallel Robots ; 2023 ; Nantes, France June 25, 2023 - June 28, 2023
03.06.2023
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch