On Solving the Forward Kinematics of the 6-6 General Parallel Manipulator with an Efficient Evolutionary Algorithm

Rolland, Luc; Chandra, Rohitash

doi:10.1007/978-3-7091-0277-0_13

Cited by 6 publications

(7 citation statements)

References 7 publications

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“…In the 3RPR problem, we found the two distinct solutions and in the 6-6 leg problem, we found all the 16 solutions as done earlier (Rolland & Chandra, 2010). This was done by running multiple experiments with different initial positions in the search space.…”

Section: Experiments and Results For The Fkp Of The 6-6 Legmentioning

confidence: 98%

“…The comparison is made with the G3-PCX EA (Rolland & Chandra, 2010) which has given the best performance when compared to hybrid genetic algorithms -simulated annealing and RCGAs (Rolland & Chandra, 2009a).…”

Section: Experiments and Resultsmentioning

confidence: 99%

“…G3-PCX has been applied to 6-leg FKPs in the past (Rolland & Chandra, 2010). It is important to highlight its strengths and limitations as studied in benchmark problems.…”

Section: Generalised Generation Gap With Parent-centric Crossovermentioning

confidence: 99%

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Global–local population memetic algorithm for solving the forward kinematics of parallel manipulators

Chandra

Rolland

2014

Connection Science

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Memetic algorithms (MA) are evolutionary computation methods that employ local search to selected individuals of the population. This work presents global-local population MA for solving the forward kinematics of parallel manipulators. A real-coded generation algorithm with features of diversity is used in the global population and an evolutionary algorithm with parent-centric crossover operator which has local search features is used in the local population. The forward kinematics of the 3RPR and 6-6 leg manipulators are examined to test the performance of the proposed method. The results show that the proposed method improves the performance of the real-coded genetic algorithm and can obtain highquality solutions similar to the previous methods for the 6-6 leg manipulator. The accuracy of the solutions and the optimisation time achieved by the methods in this work motivates for real-time implementation of the 3RPR parallel manipulator.

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Section: Experiments and Results For The Fkp Of The 6-6 Legmentioning

confidence: 98%

Section: Experiments and Resultsmentioning

confidence: 99%

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Global–local population memetic algorithm for solving the forward kinematics of parallel manipulators

Chandra

Rolland

2014

Connection Science

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“…The problem is so difficult that some authors have shown that the model for a conventional hexapod yields 40 complex and real solutions. [8][9][10][11][12] Different algorithms have been developed to compute these solutions, e.g., elimination methods, [12][13][14][15][16] continuation methods, 11,17,18 Gröbner bases methods, 19,20 interval analyses 21,22 and more recently, the application of genetic algorithms [23][24][25] and neural networks. 26,27 However, the forward displacement analysis for hexapods remains an open problem for the scientific community.…”

Section: Introductionmentioning

confidence: 99%

Kinematic analysis of a novel 2(3-RUS) parallel manipulator

et al. 2015

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SUMMARYThis paper introduces a novel 6-DOF parallel manipulator, which is composed of two 3-RUS parallel manipulators that share a common three-dimensional moving platform. Semi-analytical form solutions are easily obtained to solve the forward displacement analysis of the robot using the non-planar geometry of the moving platform, whereas the velocity, acceleration, and singularity analyses are performed using screw theory. A case study is included to show the application of the kinematic model, which is verified with the aid of a commercially available software. Simple kinematic analysis and reduced singular regions are the main benefits of the proposed parallel manipulator.

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“…For example, genetic algorithms have been used to optimal planning of experiments for calibration problem in serial robots, 33 or addressing an optimal control of parallel manipulators. 24 The optimized design of parallel mechanisms have been also studied by using differential evolution 3 or neuro-genetic algorithms. 24 The optimized design of parallel mechanisms have been also studied by using differential evolution 3 or neuro-genetic algorithms.…”

Section: Introductionmentioning

confidence: 99%

Design optimization of a cable-based parallel tracking system by using evolutionary algorithms

2014

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2015). Design optimization of a cablebased parallel tracking system by using evolutionary algorithms. Robotica, 33, pp 599-610 SUMMARYIn this paper, an optimization design of a 6 DOF parallel measuring system is analyzed. First, a closed form direct kinematics formulation based on Cayley-Menger determinants is considered in the objective function, in order to measure the manipulator singularities, then an estimation of distribution algorithm is proposed to solve the optimization problem. It is shown that the evolutionary algorithm can find close to optimal solutions for minimum pose error estimation. Additionally, these global optimizers significantly reduce the computational burden in comparison with exhaustive search and other global optimization techniques. The sensitivity of the pose error estimation in the prescribed robots' workspace is analyzed and used to guide a designer in choosing the best structural configuration. Numerical examples are discussed to show the feasibility of the proposed optimization methodology.

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On Solving the Forward Kinematics of the 6-6 General Parallel Manipulator with an Efficient Evolutionary Algorithm

Cited by 6 publications

References 7 publications

Global–local population memetic algorithm for solving the forward kinematics of parallel manipulators

Global–local population memetic algorithm for solving the forward kinematics of parallel manipulators

Kinematic analysis of a novel 2(3-RUS) parallel manipulator

Design optimization of a cable-based parallel tracking system by using evolutionary algorithms

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