Overtaking Uncertainty With Evolutionary TORCS Controllers: Combining BLX With Decreasing $\alpha$ Operator and Grand Prix Selection

Salem, Mohammed; Mora, Antonio M.; Guervós, Juan Julián Merelo

doi:10.1109/tg.2021.3072417

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Cited by 3 publications

References 30 publications

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Applying evolutionary methods for the optimization of an intrusion detection system to detect anomalies in network traffic flows

Mora,

Merino,

Hernández

et al. 2024

Advances in Computers

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Applying evolutionary methods for the optimization of an intrusion detection system to detect anomalies in network traffic flows

Mora,

Merino,

Hernández

et al. 2024

Advances in Computers

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Data-driven simulation-based decision support system for resource allocation in industry 4.0 and smart manufacturing

Mahmoodi,

Fathi,

Tavana

et al. 2024

Journal of Manufacturing Systems

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Study on the Modeling and Compensation Method of Pose Error Analysis for the Fracture Reduction Robot

Liu

Sun

et al. 2022

Micromachines

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Background: In the process of fracture reduction, there are some errors between the actual trajectory and the ideal trajectory due to mechanism errors, which would affect the smooth operation of fracture reduction. To this end, based on self-developed parallel mechanism fracture reduction robot (FRR), a novel method to reduce the pose errors of FRR is proposed. Methods: Firstly, this paper analyzed the pose errors, and built the model of the robot pose errors. Secondly, mechanism errors of FRR were converted into drive bar parameter’s errors, and the influence of each drive bar parameter on the robot pose error were analyzed. Thirdly, combining with Cauchy opposition-based learning and differential evolution algorithm (DE), an improved whale optimization algorithm (CRLWOA-DE) is proposed to compensate the end-effector’s pose errors, which could improve the speed and accuracy of fracture reduction, respectively. Results: The iterative accuracy of CRLWOA-DE is improved by 50.74%, and the optimization speed is improved by 22.62% compared with the whale optimization algorithm (WOA). Meanwhile, compared with particle swarm optimization (PSO) and ant colony optimization (ACO), CRLWOA-DE is proved to be more accurate. Furthermore, SimMechanics in the software of MATLAB was used to reconstruct the fracture reduction robot, and it was verified that the actual motion trajectory of the CRLWOA-DE optimized kinematic stage showed a significant reduction in error in both the x-axis and z-axis directions compared to the desired motion trajectory. Conclusions: This study revealed that the error compensation in FRR reset process had been realized, and the CRLWOA-DE method could be used for reducing the pose error of the fracture reduction robot, which has some significance for the bone fracture and deformity correction.

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Overtaking Uncertainty With Evolutionary TORCS Controllers: Combining BLX With Decreasing $\alpha$ Operator and Grand Prix Selection

Cited by 3 publications

References 30 publications

Applying evolutionary methods for the optimization of an intrusion detection system to detect anomalies in network traffic flows

Applying evolutionary methods for the optimization of an intrusion detection system to detect anomalies in network traffic flows

Data-driven simulation-based decision support system for resource allocation in industry 4.0 and smart manufacturing

Study on the Modeling and Compensation Method of Pose Error Analysis for the Fracture Reduction Robot

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