Concurrent redesign of an underactuated robot manipulator

Cruz-Villar, Carlos A.; Álvarez-Gallegos, Jaime; Villarreal-Cervantes, Miguel Gabriel

doi:10.1016/j.mechatronics.2008.09.002

Cited by 21 publications

(16 citation statements)

References 11 publications

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“…The last constraints involve the bound in the design variables vector p. Those are stated in (6)- (9), where the maximum and minimum values are shown in Table I: …”

Section: B Objective Functionmentioning

confidence: 99%

“…The optimization problem for the parallel robot design consists in finding the optimal design parameter vector p * which minimizes the mechanical energy of the robot (2) subject to inequality constraints related to the design such as to have a desired dextrous workspace (3), to avoid the collision between links (4)- (5) and to limit the design variable vector (6)- (9). Then, the optimization problem can be formally stated as in (10)- (11):…”

Section: Optimization Problem Statementmentioning

confidence: 99%

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Influence of the Binomial Crossover in the DE Variants Based on the Robot Design with Optimum Mechanical Energy

et al. 2015

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Abstract-Differential evolution (DE) is a powerful algorithm to find an optimal solution in real world problems. Nevertheless, the binomial crossover parameter is an important issue for the success of the algorithm. The proper selection of the binomial crossover parameter depends on the problem at hand. In this work, the effect of the binomial crossover in the DE/Rand/1/bin, DE/Best/1/Bin and DE/Current to rand/1/Bin is empirically studied and analyzed in the optimum design of the kinematic and the dynamic parameters of links for a parallel robot. The optimum design minimizes mechanical energy and consequently reduces the energy provided by the actuator. Based on the experimental results, the range of crossover parameter values that properly explores the search space is obtained. The importance of finding a proper crossover parameter is highlighted. In addition, the optimal design shows a decrease in the parallel robot mechanical energy compared with non-optimal design.Index Terms-Differential evolution, binomial crossover, optimum design, mechatronic design.

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“…The last constraints involve the bound in the design variables vector p. Those are stated in (6)- (9), where the maximum and minimum values are shown in Table I: …”

Section: B Objective Functionmentioning

confidence: 99%

Section: Optimization Problem Statementmentioning

confidence: 99%

Influence of the Binomial Crossover in the DE Variants Based on the Robot Design with Optimum Mechanical Energy

et al. 2015

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“…Recently, another search heuristic called differential evolution (DE) has shown performance superior to that of PSO and EA in the widely used benchmark problems. The main contributions of the present work is to state mechatronic design as a nonlinear dynamic optimization problem [3][4].…”

Section: Introductionmentioning

confidence: 99%

Structure-Control Design of a Parallel Robot Based on Multi-Objective Self-Adaptive Differential Evolution Algorithm

Meng¹,

Sheng²,

Zhong³

et al. 2012

Proceedings of the 2nd International Conference on Electronic and Mechanical Engineering and Information Technology (2012)

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Abstract. This paper presents a method based on a multi-objective self-adaptive differential evolution (MOSaDE) algorithm to improve the parametric reconfiguration feature in the optimal design of a parallel robot. We propose a MOSaDE algorithm, in which both trial vector generation strategies and their associated control parameter values are gradually self-adapted by learning from their previous experiences in generating promising solutions. Consequently, a more suitable generation strategy along with its parameter settings can be determined adaptively to match different phases of the search process. Furthermore, a constraint-handling mechanism is added to bias the search to the feasible region of the search space. The obtained solution will be a set of optimal geometric parameters and optimal PID control gains. The results obtained in a set of experiments performed mechatronic system show the effectiveness of the proposed approach.

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“…When knuckles of under-actuated robot hand fingers are mechanically coupled by means of planar four-bar linkage mechanism, there is one to one relationship between the finger's joint angles and its general position [4,5] . But the motion-coupled of multiple linkages cause that the nonlinear equations connected the finger's joint angles (the input of linkages) and its general position (the output of linkages) are very complex, lead into a large amount of computation, which result in a problem of low efficiency in solving the forward kinematics of the finger with traditional Newton Iteration [5,6] .…”

Section: Introductionmentioning

confidence: 99%

“…But the motion-coupled of multiple linkages cause that the nonlinear equations connected the finger's joint angles (the input of linkages) and its general position (the output of linkages) are very complex, lead into a large amount of computation, which result in a problem of low efficiency in solving the forward kinematics of the finger with traditional Newton Iteration [5,6] .…”

Section: Introductionmentioning

confidence: 99%

Virtual link-lengths approximating method for forward kinematics of multiple motion-coupled linkage mechanism

Sun

Luo

et al. 2011

Proceedings of 2011 International Conference on Electronic &Amp; Mechanical Engineering and Information Technology

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Abstrac-The forward kinematics of one kind of multiple motion-coupled linkages mechanisms were investigated, which were applied to the finger of one kind of under-actuated hand, when the finger was not touching any objects. By setting virtual link-lengths for multiple motion-coupled linkages, a numerical approximating method to solve the linkages forward kinematics was advanced. The objective was to improve the iterative speed slowed by the motion-couple of multiple linkages. In this method, these virtual link-lengths were used as several new variables in Newton Iteration to reduce the amount of derivation and computation for each differential iterative step and then the entire computing time. The operating speed had an obviously improvement in a numerical example.

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Concurrent redesign of an underactuated robot manipulator

Cited by 21 publications

References 11 publications

Influence of the Binomial Crossover in the DE Variants Based on the Robot Design with Optimum Mechanical Energy

Influence of the Binomial Crossover in the DE Variants Based on the Robot Design with Optimum Mechanical Energy

Structure-Control Design of a Parallel Robot Based on Multi-Objective Self-Adaptive Differential Evolution Algorithm

Virtual link-lengths approximating method for forward kinematics of multiple motion-coupled linkage mechanism

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