Genetic algorithm-based optimal bipedal walking gait synthesis considering tradeoff between stability margin and speed

Goswami, Dip; Vadakkepat, Prahlad; Kien, Phung duc

doi:10.1017/s026357470800475x

Cited by 56 publications

(31 citation statements)

References 28 publications

(85 reference statements)

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“…The Genetic Algorithm (GA) is the gait optimization tool which is most often used, and some modifications can be introduced to fit the specific problems of gait optimization [25,27,28]. For example, interpolating and extrapolating operators [29], two-point crossover, Gaussian mutation, overlapping populations [2], and Elitism strategy have been adopted.…”

Section: The Multiform Ec Models Adopted In Gait Optimizationmentioning

confidence: 99%

A Review of Gait Optimization Based on Evolutionary Computation

Gong

Yan

Zuo

2010

Applied Computational Intelligence and Soft Computing

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Gait generation is very important as it directly affects the quality of locomotion of legged robots. As this is an optimization problem with constraints, it readily lends itself to Evolutionary Computation methods and solutions. This paper reviews the techniques used in evolution-based gait optimization, including why Evolutionary Computation techniques should be used, how fitness functions should be composed, and the selection of genetic operators and control parameters. This paper also addresses further possible improvements in the efficiency and quality of evolutionary gait optimization, some problems that have not yet been resolved and the perspectives for related future research.

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Section: The Multiform Ec Models Adopted In Gait Optimizationmentioning

confidence: 99%

A Review of Gait Optimization Based on Evolutionary Computation

Gong

Yan

Zuo

2010

Applied Computational Intelligence and Soft Computing

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“…The method developed by D. Huan, through the Genetic Algorithm (GA), optimized the gait generator parameters as to help robot move steadily with the least amount of energy [7]. Dip et al [8] exhibited steady gait for biped at constant velocity using the sine wave generator. Maximo et al [9] introduced a new stable and quick model-free gait with specific arms movement for biped robots.…”

Section: Introductionmentioning

confidence: 99%

“…Khusainov et al [10] successfully combined kinematics and dynamics approaches in gait optimization for humanoid robot locomotion. The fact is that, nowadays, intelligent algorithms are being increasingly applied in this domain to optimize the gait generator parameters for humanoid robots such as GA [8], Particle Swarm Optimization (PSO) algorithm [11], Modified Differential Evolution (MDE) algorithm [12], Central Force Optimization (CFO) algorithm [13]. Shaffi in [14] introduced the humanoid robot achieved a stable gait by using the Fourier seriesbased gait generator.…”

Section: Introductionmentioning

confidence: 99%

Optimal Walking Gait Generator for Biped Robot Using Modified Jaya Optimization Technique

Ánh¹,

Huan²

2020

IJCIS

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This paper treats the optimization of the biped walking trajectory that can be used as a reference trajectory for control. The biped robot is modeled as a kinetic chain of 11 links connected by 10 joints. The inverse kinematics of the biped is derived for the specified positions of the hips and feet. The objective is to optimize the biped robot able to stably and naturally walking with preset foot-lift magnitude (or preset hip-shift, or preset step-length). The stability of the biped robot is quantified by the distance between the ZMP and the foot center in the step cycle, which represents the first objective function. Additionally, for the biped robot to follow the preset foot-lift value, the difference between the magnitude of foot-lift value and the foot-lift preset value represents the second objective function. Specifically, we minimize the value of the two objective functions by considering the gait parameters of biped robot as variables. The new Jaya optimization algorithm is innovatively applied to optimize the biped gait parameters as to ensure the biped robot walking robustly and steadily. The efficiency of the proposed Jaya-based identification method is compared with the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO), the Central Force Optimization (CFO) and improved Differential Evolution (DE) [Modified Differential Evolution (MDE)] algorithms. The simulation results tested on the real small-sized biped robot system HUBOT-4 demonstrate that the novel proposed algorithm offers an efficient and stable gait for biped robot with precise foot-lift value.

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“…Khusainov et al 10 successfully combined kinematics and dynamics approaches in biped gait optimization for humanoid robot locomotion. Moreover, nowadays, intelligent algorithms are being increasingly applied in this domain to optimize the gait generator parameters for humanoid robots such as GA, 8 particle swarm optimization (PSO) algorithm, 11 modified differential evolution (MDE) algorithm, 12 and central force optimization (CFO) algorithm. 13 Shafii et al 14 introduced a humanoid robot that achieved a stable gait using the Fourier seriesbased gait generator.…”

Section: Introductionmentioning

confidence: 99%

Optimal nature-walking gait for humanoid robot using Jaya optimization algorithm

Huan

Ánh

Kien

2019

Advances in Mechanical Engineering

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This article proposes a new method used to optimize the design process of nature-walking gait generator that permits biped robot to stably and naturally walk with preset foot-lift magnitude. The new Jaya optimization algorithm is innovatively applied to optimize the biped gait four key parameters initiatively applied to ensure the uncertain nonlinear humanoid robot walks robustly and steadily. The efficiency of the proposed Jaya-based identification approach is compared with the central force optimization and improved differential evolution (modified differential evolution) algorithms. The simulation and experimental results tested on the original small-sized biped robot HUBOT-4 convincingly demonstrate that the novel proposed algorithm offers an efficient and stable gait for humanoid robots with precise height of foot-lift value.

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Genetic algorithm-based optimal bipedal walking gait synthesis considering tradeoff between stability margin and speed

Cited by 56 publications

References 28 publications

A Review of Gait Optimization Based on Evolutionary Computation

A Review of Gait Optimization Based on Evolutionary Computation

Optimal Walking Gait Generator for Biped Robot Using Modified Jaya Optimization Technique

Optimal nature-walking gait for humanoid robot using Jaya optimization algorithm

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