Comparison Study of the PSO and SBPSO on Universal Robot Trajectory Planning

Kazim, Issraa Jwad; Tan, Yuegang; Li, Ruiya

doi:10.3390/app12031518

Cited by 3 publications

(4 citation statements)

References 34 publications

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“…T robot , which represents the pose of the UR5 robot, is obtained via Equation (11). The UR5 robot's pose should satisfy Equation (12), and the D-H parameters of the UR5 robot are shown in Table 1.…”

Section: Nine-axis Ur5 Robot Forward Kinematics Modelmentioning

confidence: 99%

“…The constraint matrix of the UR5 robot, which is shown The main idea of the closed-form solution is creating the constraint equation established by matrix changes. The constraint matrix of the UR5 robot, which is shown in Equation (15), is established in accordance with Equation (11). The third row of the left and right sides of Equation ( 15) is expanded to establish Equation (16).…”

Section: Inverse Solution Model For Recommended Regionsmentioning

confidence: 99%

“…Kazim, I.J. et al compared improving the artificial potential field (APF) by the traditional particle swarm optimization (PSO) algorithm and the serendipitybased PSO (SBPSO) algorithm to control the path of a universal robot UR5 with collision avoidance [11]. Kazim, I.J.…”

Section: Introductionmentioning

confidence: 99%

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An Algorithm for Painting Large Objects Based on a Nine-Axis UR5 Robotic Manipulator

et al. 2022

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An algorithm for automatically planning trajectories designed for painting large objects is proposed in this paper to eliminate the difficulty of painting large objects and ensure their surface quality. The algorithm was divided into three phases, comprising the target point acquisition phase, the trajectory planning phase, and the UR5 robot inverse solution acquisition phase. In the target point acquisition phase, the standard triangle language (STL) file, algorithm of principal component analyses (PCA), and k-dimensional tree (k-d tree) were employed to obtain the point cloud model of the car roof to be painted. Simultaneously, the point cloud data were compressed as per the requirements of the painting process. In the trajectory planning phase, combined with the maximum operating space of the UR5 robot, the painting trajectory of the target points was converted into multiple traveling salesman problem (TSP) models, and each TSP model was created with a genetic algorithm (GA). In the last phase, in conformity with the singularities of the UR5 robot’s motion space, the painting trajectory was divided into a recommended area trajectory and a non-recommended area trajectory and created by the analytical method and sequential quadratic programming (SQP). Finally, the proposed algorithm for painting large objects was deployed in a simulation experiment. Simulation results showed that the accuracy of the algorithm could meet the requirements of painting technology, and it has promising engineering practicability.

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Section: Nine-axis Ur5 Robot Forward Kinematics Modelmentioning

confidence: 99%

Section: Inverse Solution Model For Recommended Regionsmentioning

confidence: 99%

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An Algorithm for Painting Large Objects Based on a Nine-Axis UR5 Robotic Manipulator

et al. 2022

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“…Building a digital twin of a magnetic bearing system requires accurate and detailed models of the system and real-time sensor data from the physical system [5,6]. The digital twin must be able to accurately simulate the physical behavior of the system, including the electromagnetic forces that are used to levitate the rotor [7].…”

Section: Introductionmentioning

confidence: 99%

Modeling of a Digital Twin for Magnetic Bearings

Taha

2023

Applied Sciences

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As an essential enabling technology to realize advanced concepts such as digitization, intelligence, and service, information technology plays a critical role in shaping modern society and driving innovation across various industries and domains. The concept of the digital twin is attracting attention from academics and industry, and how to apply it in various fields. In this paper, the performance of the magnetic bearing system may be simulated in real-time using a digital twin, especially the resulting vibration from the unbalanced rotor mass, which caused a drop in performance and a high risk of system instability and potential safety accidents. It is suggested to use a model-data combination driven digital twin model to examine its dynamic characteristics and vibration mechanism. The vibration data of the magnetic bearing was collected through experiments and compared with the data derived from the simulation results. The efficiency of the suggested strategy is demonstrated by confirming that digitally anticipated vibration signals are consistent with physical space measurements. The result shows that the fine digital twin geometric model of magnetic bearing is more consistent with the actual operation. By allowing the identification of problems before they become critical, using a digital twin may increase the dependability of magnetic bearings while reducing the possibility of unexpected downtime or failures.

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A way to combine music education and intelligent algorithms to cultivate innovative musical talents

Fang

2024

Applied Mathematics and Nonlinear Sciences

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The arrival of the intelligent era makes intelligent music education a reality, which is a product of the combination of intelligent technology and music education. The article starts with the intelligent transformation of music education, analyzes the talent cultivation mode of music education, and establishes the intelligent classroom teaching mode of music education through the use of intelligent technology. Combined with the data of students’ online music learning behavior, a personalized music learning path model is established, and a nonlinear factor is introduced to optimize the SBPSO intelligent algorithm in order to realize the accurate recommendation of a personalized learning path. A DFN model for the automatic generation of music accompaniment was established based on the Flow model, and simulation analysis and teaching experiments were carried out to analyze the effectiveness of the above methods in music-intelligent classroom teaching. The convergence value of the NFSBPSO algorithm was in the range of 0.026~0.043, and the discrepancy between the mean value of the note length of the accompaniment generated by the DFN model and that of real data was only 0.35% and the total average score of the generated accompaniment was 7.0%. Accompaniment had an overall mean score of 7.23. The observation group scored 83.64 on their final music course grade, which was 11.46 points more than the control group’s average grade. Combining music education with intelligent algorithms can achieve intelligent transformations in music education and improve the quality of talent cultivation.

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Comparison Study of the PSO and SBPSO on Universal Robot Trajectory Planning

Cited by 3 publications

References 34 publications

An Algorithm for Painting Large Objects Based on a Nine-Axis UR5 Robotic Manipulator

An Algorithm for Painting Large Objects Based on a Nine-Axis UR5 Robotic Manipulator

Modeling of a Digital Twin for Magnetic Bearings

A way to combine music education and intelligent algorithms to cultivate innovative musical talents

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