A multi-objective optimization design method of shift manipulator for robot driver using SA-PSA View Full Text


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Article Info

DATE

2022-07-07

AUTHORS

Gang Chen, Xinyao Xu, Liangmo Wang, Weigong Zhang

ABSTRACT

With the widespread use of robots in the world, including rescue operations and special surgeries, the precise design of robots is of particular importance. The shift manipulator is a part of the robot driver structure which is composed of a two-degree of freedom parallel mechanism with electric cylinders. The singularity analysis and inertia torque analysis are conducted based on the kinematic and dynamic models. The integrated design variables for multi-objective optimization are proposed to evaluate the kinematic and dynamic performance of the manipulator. Given dimensional parameters as design variables and geometric constraints in a moving area, the multi-objective integrated optimization model is established and solved by the Simulated Annealing Particle Swarm Algorithm (SA-PSA). Furthermore, the optimized performance is compared with different optimal methods, and the effectiveness of the presented method using SA-PSA is verified by performance simulations and test. The results demonstrate that the kinematic and dynamic performances are improved 22.22% through minimizing two integrated design variables. More... »

PAGES

204

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Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00158-022-03301-1

DOI

http://dx.doi.org/10.1007/s00158-022-03301-1

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