Experimental Studies of Neural Network Control for One-Wheel Mobile Robot

Kim, P. K.; Jung, Seul

doi:10.1155/2012/194397

Cited by 11 publications

(4 citation statements)

References 13 publications

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“…The work [12] presents the development and control of a disc-typed one-wheel mobile robot, called GYROBO. Two actuators are used for balancing control by virtue of gyro effect and one actuator for driving movements.…”

Section: Impact Of Vigilancementioning

confidence: 99%

Control of autonomous robot behavior using data filtering through adaptive resonance theory

Barton

Volná

Kotyrba

2017

Vietnam J Comput Sci

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The aim of the article is to use neural networks to control autonomous robot behavior. The type of the controlling neural network was chosen a backpropagation neural network with a sigmoidal transfer function. The focus in this article is put on the use adaptive resonance theory (ART1) for data filtering. ART1 is used for preprocessing of the training set. This allows finding typical patterns in the full training set and thus covering the whole space of solutions. The neural network adapted by a reduced training set has a greater ability of generalization. The work also discusses the influence of vigilance parameter settings for filtering the training set. The proposed approach to data filtering through ART1 is experimentally verified to control the behavior of an autonomous robot in an unknown environment with varying degrees of difficulty regarding the location of obstacles. All obtained results are evaluated in the conclusion.

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Section: Impact Of Vigilancementioning

confidence: 99%

Control of autonomous robot behavior using data filtering through adaptive resonance theory

Barton

Volná

Kotyrba

2017

Vietnam J Comput Sci

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“…Undeniably, they will be utilized in industry as an alternative to the skilled workforce doing high-risk activities in the near future. To control robots for a variety of challenging tasks, researchers have used efficient robust controllers, such as practical velocity tracking control [ 4 ], dynamic state feedback control [ 5 ], fuzzy PD control [ 6 ], and neural network control [ 7 ]. Specifically, Solís-Perales and Peón-Escalante [ 8 ] used robust adaptive tracking control for a class of robot manipulators having model uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Pareto Design of State Feedback Tracking Control of a Biped Robot via Multiobjective PSO in Comparison with Sigma Method and Genetic Algorithms: Modified NSGAII and MATLAB’s Toolbox

Mahmoodabadi

Taherkhorsandi

Bagheri

2014

The Scientific World Journal

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An optimal robust state feedback tracking controller is introduced to control a biped robot. In the literature, the parameters of the controller are usually determined by a tedious trial and error process. To eliminate this process and design the parameters of the proposed controller, the multiobjective evolutionary algorithms, that is, the proposed method, modified NSGAII, Sigma method, and MATLAB's Toolbox MOGA, are employed in this study. Among the used evolutionary optimization algorithms to design the controller for biped robots, the proposed method operates better in the aspect of designing the controller since it provides ample opportunities for designers to choose the most appropriate point based upon the design criteria. Three points are chosen from the nondominated solutions of the obtained Pareto front based on two conflicting objective functions, that is, the normalized summation of angle errors and normalized summation of control effort. Obtained results elucidate the efficiency of the proposed controller in order to control a biped robot.

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“…Fruitful research outcomes about a single-wheel mobile robot, Gyrover have been summarized as a book [6]. Other research activities on a single-wheel mobile robot can also be found in the literature, but they are not many [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…A history of implementing Gyrobo has been presented in the paper [9]. A neural network control technique is applied to control the balancing angle as well as trajectory tracking tasks [10]. One of difficulties of implementing a single-wheel robot is the mechanical design to have a symmetrical structure in the body and to generate enough gyro-effect to raise the whole system up.…”

Section: Introductionmentioning

confidence: 99%

Synchronization of two flywheels for stable balancing control of one-wheel transportation vehicle: Gyrocycle

Bae

Jung

2013

2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

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This paper presents the simple method for synchronizing the motion of two flywheels located in a one-wheel transportation vehicle called Gyrocycle. The vehicle balances itself by the gyro effect induced by two flywheels inside the Gyrocycle. Asymmetry between two flywheels reduces gyro effect and causes the unstable balancing performance at last. In this paper, a simple method is proposed to synchronize the motion of two flywheels. Experimental studies are conducted to confirm the proposed synchronization method.

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Experimental Studies of Neural Network Control for One-Wheel Mobile Robot

Cited by 11 publications

References 13 publications

Control of autonomous robot behavior using data filtering through adaptive resonance theory

Control of autonomous robot behavior using data filtering through adaptive resonance theory

Pareto Design of State Feedback Tracking Control of a Biped Robot via Multiobjective PSO in Comparison with Sigma Method and Genetic Algorithms: Modified NSGAII and MATLAB’s Toolbox

Synchronization of two flywheels for stable balancing control of one-wheel transportation vehicle: Gyrocycle

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