A universal index and an improved PSO algorithm for optimal pose selection in kinematic calibration of a novel surgical robot

Wang, Weidong; Song, Huajian; Yan, Zhiyuan; Sun, Lining; Du, Zhijiang

doi:10.1016/j.rcim.2017.09.011

Cited by 61 publications

(26 citation statements)

References 22 publications

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“…PSO was used in many optimization problems such as solar cell design [46] , [47] , electrical motor design [48] , and surgical robot applications [49] .…”

Section: Preliminariesmentioning

confidence: 99%

Analyzing COVID-19 virus based on enhanced fragmented biological Local Aligner using improved Ions Motion Optimization algorithm

Issa

Elaziz

2020

Applied Soft Computing

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SARS-CoV-2 (COVID-19) virus is a havoc pandemic that infects millions of people over the world and thousands of infected cases dead. So, it is vital to propose new intelligent data analysis tools and enhance the existed ones to aid scientists in analyzing the COVID-19 virus. Fragmented Local Aligner Technique (FLAT) is a data analysis tool that is used for detecting the longest common consecutive subsequence (LCCS) between a pair of biological data sequences. FLAT is an aligner tool that can be used to find the LCCS between COVID-19 virus and other viruses to help in other biochemistry and biological operations. In this study, the enhancement of FLAT based on modified Ions Motion Optimization (IMO) is developed to produce acceptable LCCS with efficient performance in a reasonable time. The proposed method was tested to find the LCCS between Orflab poly-protein and surface glycoprotein of COVID-19 and other viruses. The experimental results demonstrate that the proposed model succeeded in producing the best LCCS against other algorithms using real LCCS measured by the SW algorithm as a reference.

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“…PSO was used in many optimization problems such as solar cell design [46] , [47] , electrical motor design [48] , and surgical robot applications [49] .…”

Section: Preliminariesmentioning

confidence: 99%

Analyzing COVID-19 virus based on enhanced fragmented biological Local Aligner using improved Ions Motion Optimization algorithm

Issa

Elaziz

2020

Applied Soft Computing

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“…in the positioning error of manipulator, they will significantly affect calibration performance [11]. In fact, the unmodeled errors are difficult to eliminate.…”

Section: Introductionmentioning

confidence: 99%

“…The fifth index is based on A-optimal design (expressed as O 5 ) [17]; it also reflects the overall observability of configurations. The newest index is improved p -optimality index (is expressed as O 6 ) [11], and both O 1 , O 3 , and O 5 , can be regarded as special cases of O 6 .…”

Section: Introductionmentioning

confidence: 99%

“…After establishing index to evaluate configurations' quality, the next step is to design configuration optimization algorithm. Scholars have applied many algorithms to optimize configurations, including DETMAX [18]- [20], simulated annealing (SA) [21], genetic algorithm (GA) [22]- [23], particle swarm optimization (PSO) [11], etc. DETMAX [24] is one of the most widely used algorithms for calibration configuration optimization.…”

Section: Introductionmentioning

confidence: 99%

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Configuration Optimization for Manipulator Kinematic Calibration Based on Comprehensive Quality Index

et al. 2019

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Kinematic calibration performance is heavily dependent on two factors-the ability of calibration configurations mapping kinematic parameter errors, and the un-modeled errors including joint clearance, thermal expansion, and measurement noise. Therefore, this paper deals with the calibration configuration optimization to reduce the impact of the two factors on calibration performance. We pay particular attention to establish an index for evaluating calibration configuration's quality. Different from other works, the proposed comprehensive quality index can simultaneously reflect configurations' observability and globality. Furthermore, the numerical methods are used to analyze the relationships between the comprehensive quality index and configuration number, and the relationships between calibration performance and configuration number. Based on the above relationships, we provide a feasible solution for determining the calibration configuration number of a specific manipulator. Based on the above work, configuration optimization model is established and solved by particle swarm optimization. The simulation of an eight degree-of-freedom manipulator illustrates the advantages of the proposed method. In 100 calibration simulations, optimized configurations perform better than random configurations, with the position accuracy increased by 43.86% and the attitude accuracy increased by 14.29%.

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“…Fan et al [13] conducted the parameter identification of a parallel mechanism based on genetic algorithm. Wang et al [14] proposed a universal index and an improved PSO algorithm for optimal pose selection. Shi et al [15] proposed a quantum particle swarm optimization (QPSO) algorithm based on the path-planning method, so that the base position and the end position can simultaneously reach the desired state.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Optimal Kinematic Parameter Identification for an Industrial Robot Based on BPNN‐PSO

et al. 2018

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A novel hybrid algorithm that employs BP neural network (BPNN) and particle swarm optimization (PSO) algorithm is proposed for the kinematic parameter identification of industrial robots with an enhanced convergence response. The error model of the industrial robot is established based on a modified Denavit-Hartenberg method and Jacobian matrix. Then, the kinematic parameter identification of the industrial robot is transformed to a nonlinear optimization in which the unknown kinematic parameters are taken as optimal variables. A hybrid algorithm based on a BPNN and the PSO is applied to search for the optimal variables which are used to compensate for the error of the kinematic parameters and improve the positioning accuracy of the industrial robot. Simulations and experiments based on a realistic industrial robot are all provided to validate the efficacy of the proposed hybrid identification algorithm. The results show that the proposed parameter-identification method based on the BPNN and PSO has fewer iterations and faster convergence speed than the standard PSO algorithm.

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A universal index and an improved PSO algorithm for optimal pose selection in kinematic calibration of a novel surgical robot

Cited by 61 publications

References 22 publications

Analyzing COVID-19 virus based on enhanced fragmented biological Local Aligner using improved Ions Motion Optimization algorithm

Analyzing COVID-19 virus based on enhanced fragmented biological Local Aligner using improved Ions Motion Optimization algorithm

Configuration Optimization for Manipulator Kinematic Calibration Based on Comprehensive Quality Index

Hybrid Optimal Kinematic Parameter Identification for an Industrial Robot Based on BPNN‐PSO

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