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Erschienen in:
Critical Review and Progress of Adaptive Controller Design for Robot Arms Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

Multi-objective Optimization of a Parallel Fine-tuning Manipulator for Segment Assembly Robots in Shield Tunneling Machines

verfasst von : Guohua Cui, Haidong Zhou, Yanwei Zhang, Haibin Zhou

Erschienen in: Mechatronics and Robotics Engineering for Advanced and Intelligent Manufacturing

Verlag: Springer International Publishing

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Abstract

A new 6-DOF serial/parallel hybrid segment assembly robot that includes a 3-DOF redundant parallel orientation fine-tuning manipulator is developed. Redundancy can, in general, improve the ability and performance of parallel manipulators by implementing the redundant degree of freedom to optimize the objective function. A multi-objective optimization model of the proposed manipulator is likewise established with consideration of kinematic and dynamic dexterity, load-bearing capacity, stiffness, and actuating force equilibrium. To accomplish optimization, a new multi-objective optimization method is proposed using the application Isight, which integrates various engineering softwares. Results indicate that this method can automatically accomplish the calculation of the kinematic and dynamic performance index, modeling, and solving using Isight. Thus, decision makers can select the proper optimal solution based on the obtained Pareto plot and Pareto frontier. Finally, optimizing its design variables considerably improves the performance of the proposed parallel manipulator.

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Vorheriges Kapitel Indoor Localization for Swarm Robotics with Communication Metrics Without Initial Position Information
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Metadaten
Titel
Multi-objective Optimization of a Parallel Fine-tuning Manipulator for Segment Assembly Robots in Shield Tunneling Machines
verfasst von
Guohua Cui
Haidong Zhou
Yanwei Zhang
Haibin Zhou
Copyright-Jahr
2017
Buch
Mechatronics and Robotics Engineering for Advanced and Intelligent Manufacturing

Print ISBN: 978-3-319-33580-3

Electronic ISBN: 978-3-319-33581-0

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-33581-0_17

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