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Open AccessArticle

Shape Design Optimization of a Robot Arm Using a Surrogate-Based Evolutionary Approach

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Department of Mechanical Engineering, National Chiao Tung University, No. 1001, University Road, Hsinchu 30010, Taiwan
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Precision Machinery Research & Development Centre (PMC), No. 27, 37th Road, Taichung Industrial Park, Taichung 40768, Taiwan
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(7), 2223; https://doi.org/10.3390/app10072223
Received: 19 January 2020 / Revised: 13 March 2020 / Accepted: 17 March 2020 / Published: 25 March 2020
(This article belongs to the Section Mechanical Engineering)
In the design optimization of robot arms, the use of simulation technologies for modeling and optimizing the objective functions is still challenging. The difficulty is not only associated with the large computational cost of high-fidelity structural simulations but also linked to the reasonable compromise between the multiple conflicting objectives of robot arms. In this paper we propose a surrogate-based evolutionary optimization (SBEO) method via a global optimization approach, which incorporates the response surface method (RSM) and multi-objective evolutionary algorithm by decomposition (the differential evolution (DE ) variant) (MOEA/D-DE) to tackle the shape design optimization problem of robot arms for achieving high speed performance. The computer-aided engineering (CAE) tools such as CAE solvers, computer-aided design (CAD) Inventor, and finite element method (FEM) ANSYS are first used to produce the design and assess the performance of the robot arm. The surrogate model constructed on the basis of Box–Behnken design is then used in the MOEA/D-DE, which includes the process of selection, recombination, and mutation, to optimize the robot arm. The performance of the optimized robot arm is compared with the baseline one to validate the correctness and effectiveness of the proposed method. The results obtained for the adopted example show that the proposed method can not only significantly improve the robot arm performance and save computational cost but may also be deployed to solve other complex design optimization problems. View Full-Text
Keywords: surrogate-based evolutionary optimization; response surface method; Box–Behnken design; multi-objective evolutionary algorithm; robot arm surrogate-based evolutionary optimization; response surface method; Box–Behnken design; multi-objective evolutionary algorithm; robot arm
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MDPI and ACS Style

Hsiao, J.C.; Shivam, K.; Chou, C.L.; Kam, T.Y. Shape Design Optimization of a Robot Arm Using a Surrogate-Based Evolutionary Approach. Appl. Sci. 2020, 10, 2223.

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