Amoako-Frimpong Samuel Yaw, Matthew Messina, Henry Medeiros, Jeremy Marvel, Roger V. Bostelman
Mobile manipulators are a potential solution to the increasing need for additional flexibility and mobility in industrial applications. However, they tend to lack the accuracy and precision achieved by fixed manipulators, especially in scenarios where both the manipulator and the autonomous vehicle move simultaneously. This paper analyzes the problem of dynamically evaluating the positioning error of mobile manipulators. In particular, it investigates the use of Bayesian methods to predict the position of the end-effector in the presence of uncertainty propagated from the mobile platform. The precision of the mobile manipulator is evaluated through its ability to intercept retroreflective markers using a photoelectric sensor attached to the end-effector. Compared to a deterministic search approach, we observed improved robustness with comparable search times, thereby enabling effective calibration of the mobile manipulator.
, Messina, M.
, Medeiros, H.
, Marvel, J.
and Bostelman, R.
Stochastic Search Methods for Mobile Manipulators, Procedia Manufacturing, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=928687
(Accessed October 16, 2021)