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Stochastic Search Methods for Mobile Manipulators



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.
Procedia Manufacturing


mobile manipulator, dynamic, stochastic search, deterministic search, performance measurement, autonomous vehicle


Yaw, A. , Messina, M. , Medeiros, H. , Marvel, J. and Bostelman, R. (2018), Stochastic Search Methods for Mobile Manipulators, Procedia Manufacturing, [online], (Accessed June 19, 2024)


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Created November 29, 2018, Updated October 12, 2021