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Novel Reconfigurable Walking Machine Tool Enables Symmetric and Nonsymmetric Walking Configurations

Camacho-Arreguin, Josue Israel; Wang, Mingfeng; Russo, Matteo; Dong, Xin; Axinte, Dragos

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Authors

Josue Israel Camacho-Arreguin

Mingfeng Wang

Matteo Russo

DRAGOS AXINTE dragos.axinte@nottingham.ac.uk
Professor of Manufacturing Engineering



Abstract

Current research on walking robots strives to achieve a higher efficiency, a better load capacity, and an increased adaptability. Parallel kinematic manipulators (PKMs) are characterized by high payload and accuracy, but conventional PKMs with fixed configurations are limited to constrained workspaces in known structured environments. In this article, we propose a parallel reconfigurable walking machine tool that overcomes these limits by adapting its configuration and gaits to different scenarios. A lightweight and compact positioning system with shape memory alloy actuation is presented to achieve reconfiguration capabilities. Furthermore, kinematic, stability, and force analyses are reported to determine the optimal walking gaits in three different scenarios (with inclined slopes at different angles) and four robot configurations. Finally, a set of experiments with the physical prototype validates the proposed models. The results show that symmetric configurations present a better performance at lower ground inclinations (0.5% error), whereas asymmetric configurations can climb on slope conditions that would prevent the use of conventional PKMs (18% or 10°).

Citation

Camacho-Arreguin, J. I., Wang, M., Russo, M., Dong, X., & Axinte, D. (2022). Novel Reconfigurable Walking Machine Tool Enables Symmetric and Nonsymmetric Walking Configurations. IEEE/ASME Transactions on Mechatronics, https://doi.org/10.1109/TMECH.2022.3183689

Journal Article Type Article
Acceptance Date Jun 12, 2022
Online Publication Date Jul 1, 2022
Publication Date Jul 1, 2022
Deposit Date Jul 5, 2022
Publicly Available Date Jul 6, 2022
Journal IEEE/ASME Transactions on Mechatronics
Print ISSN 1083-4435
Electronic ISSN 1941-014X
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1109/TMECH.2022.3183689
Keywords Electrical and Electronic Engineering; Computer Science Applications; Control and Systems Engineering
Public URL https://nottingham-repository.worktribe.com/output/8771660
Publisher URL https://ieeexplore.ieee.org/document/9812939

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