On motion optimization of robotic manipulators with strong nonlinear dynamic coupling using support area level set algorithm

Li, Zhijun; Yang, Kun; Bogdan, Stjepan; Xu, Bugong

doi:10.1007/s12555-011-9212-8

Cited by 17 publications

(5 citation statements)

References 17 publications

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“…At present, the more mainstream image encryption technology is mainly to apply the chaotic systems. For example, Li [4] proposed a pixel shift transform coupling dynamic harmony search optimization mechanism for image encryption. It used a pixel shift transform model and clear pixels to implement image scrambling.…”

Section: Introductionmentioning

confidence: 99%

Hybrid chaotic system-oriented artificial fish swarm neural network for image encryption

2021

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According to the research works of the references on chaotic cryptanalysis, many recent chaotic image encryption algorithms cannot resist chosen-plaintext attacks. Although some chaotic image encryption algorithms introduce plain-image information, they still violate some design requirements of modern cryptosystems. The traditional image encryption algorithm has the disadvantages of low security and time-consuming. Therefore, after analyzing many literatures related to chaotic image encryption and aiming to improve the security of ciphertext and effectively resist plaintext attack, we propose a hybrid chaotic system-oriented artificial fish swarm neural network method for image encryption. Firstly, based on the nonlinear combination theory, the Logistic, Tent and Sine mappings are used to design the hybrid complex chaotic system. According to the pixel value of plaintext, it generates the initial value to output the chaotic sequence. Taking a chaotic sequence as the input layer, the artificial neural network is introduced to train and learn the chaotic sequence. It eliminates the chaotic periodicity and outputs the neural network sequence. The artificial fish swarm algorithm is used to optimize the initial weight and threshold of the Elman neural network. The set obfuscation method is defined to scramble the plaintext. A quantization method is constructed to quantify the neural network sequence and obtain the key flow. The mixed images are classified, the key flow is combined, the pixel value is changed and the ciphertext is output by designing the piecewise diffusion technology. Experimental results show that compared with the current state-of-the-art image encryption methods, the proposed algorithm has higher security and resist plaintext attack ability.

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Section: Introductionmentioning

confidence: 99%

Hybrid chaotic system-oriented artificial fish swarm neural network for image encryption

2021

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“…Other related advanced procedures include e.g. the generation of cyclic motions for dual-arm robots using neural networks and quadratic programing [23], the consideration of the robot dynamics in the motion planning by transforming the problem into an optimization of a non-linear fitness function [24] or the use of movement primitives based on a model of the triangle defined by the human upperarm and forearm [25].…”

Section: Introductionmentioning

confidence: 99%

Motion Planning by Demonstration With Human-Likeness Evaluation for Dual-Arm Robots

Garcia

Rosell

Suárez

2019

IEEE Trans. Syst. Man Cybern, Syst.

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Abstract-The paper presents a planning procedure that allows an anthropomorphic dual-arm robotic system to perform a manipulation task in a natural human-like way by using demonstrated human movements. The key idea of the proposal is to convert the demonstrated trajectories into attractive potential fields defined over the configuration space and then use an RRT * -based planning algorithm that minimizes a path-cost function designed to bias the tree growth towards the human-demonstrated configurations. The paper presents a description of the proposed approach as well as results from a conceptual and a real application example, the latter using a real anthropomorphic dual-arm robotic system. A path-quality measure, based on first-order synergies (correlations between joint velocities) obtained from real human movements, is also proposed and used for evaluation and comparison purposes. The obtained results show that the paths obtained with the proposed procedure are more human-like.

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“…Determining solutions of system variables that jointly satisfy multiple objectives in presence of noise is an important issue in the realm of optimization algorithms. These optimization problems are usually referred to as noisy multi-objective optimization [25,45].…”

Section: Introductionmentioning

confidence: 99%

Extending multi-objective differential evolution for optimization in presence of noise

Rakshit

Konar

2015

Information Sciences

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On motion optimization of robotic manipulators with strong nonlinear dynamic coupling using support area level set algorithm

Cited by 17 publications

References 17 publications

Hybrid chaotic system-oriented artificial fish swarm neural network for image encryption

Hybrid chaotic system-oriented artificial fish swarm neural network for image encryption

Motion Planning by Demonstration With Human-Likeness Evaluation for Dual-Arm Robots

Extending multi-objective differential evolution for optimization in presence of noise

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