A General Robot Inverse Kinematics Solution Method Based on Improved PSO Algorithm

Liu, Yiyang; Xi, Jiali; Bai, Hongfei; Wang, Zhining; Sun, Liangliang

doi:10.1109/access.2021.3059714

Cited by 64 publications

(25 citation statements)

References 24 publications

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“…Although many articles (Yiyang et al, 2021 ) use many test functions to test the performance of PSO algorithm, but in this paper, MOFOPSO algorithm is proposed to overcome the drawbacks of poor accuracy, low efficiency. SO three test functions are chosen for the algorithm performance test, including Ackely function, Rastrigin function, and Griewangk function to investigate the shortcomings of classical PSO algorithms, such as slow convergence speed and falling into local optimum.…”

Section: Algorithm Performance Testmentioning

confidence: 99%

Inverse Kinematics Solution of 6-DOF Manipulator Based on Multi-Objective Full-Parameter Optimization PSO Algorithm

Luo

Chu

et al. 2022

Front. Neurorobot.

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A multi-objective full-parameter optimization particle swarm optimization (MOFOPSO) algorithm is proposed in this paper to overcome the drawbacks of poor accuracy, low efficiency, and instability of the existing algorithms in the inverse kinematics(IK) solution of the manipulator. In designing the multi-objective function, the proposed algorithm considers the factors such as position, posture, and joint. To improve PSO, the proposed algorithm comprehensively analyzes all factors affecting the global and local searching abilities. Based on this, the initial population is designed following the localized uniform distribution method. Meanwhile, the inertia weight, asynchronous learning factor, and time factor are respectively designed by introducing the iteration factor. Finally, this paper tests the performance of MOFOPSO with three typical functions to obtain a better inverse kinematics solution of the 6-DOF manipulator. Also, six other algorithms are taken for performance comparison. The experimental results indicate that the proposed method not only ensures the stability of the manipulator but also achieves high accuracy and efficiency in solving the inverse kinematics of the 6-DOF manipulator.

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Section: Algorithm Performance Testmentioning

confidence: 99%

Inverse Kinematics Solution of 6-DOF Manipulator Based on Multi-Objective Full-Parameter Optimization PSO Algorithm

Luo

Chu

et al. 2022

Front. Neurorobot.

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“…Then, the CMA-ES algorithm is used to solve a real-time path tracking problem, and a good application effect is obtained. Yiyang et al 33 proposed an improved PSO algorithm to solve the robot inverse kinematics solution, and verified the excellent performance of the algorithm in the NJ-220 general-purpose robot. Dereli and Koker 34 proposed a variant of the PSO algorithm (IW-PSO), the IW-PSO algorithm is very successful in obtaining the optimal inverse kinematics solution.…”

Section: Introductionmentioning

confidence: 95%

A hybrid improved BRO algorithm and its application in inverse kinematics of 7R 6DOF robot

Zhang

Song

et al. 2022

Advances in Mechanical Engineering

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To advance the calculation performance of the battle royale optimization algorithm (BRO), a hybrid improved BRO algorithm (HBC) is proposed in this paper. The level mechanism of the chicken swarm optimization algorithm (CSO) is integrated into the BRO algorithm to divide all into elite players and ordinary players, and the level relationship of different players is established. Then, an elite player update method of random exploring and directional update in a small range is proposed to improve the development ability. The update method of ordinary players improved, the update mechanism of elite random guidance is introduced to make full use of the excellent location information in the population. The performance verification experiment of the HBC algorithm is carried out on 20 benchmark functions and a practical project. Comparing with several other algorithms, the computational performance of the HBC algorithm is the best. Furthermore, the HBC algorithm is applied to solve the inverse kinematics of the 7R 6DOF robot. The experimental results show that the HBC algorithm effectively improves the average convergence accuracy and reduces the running time, compared with the BRO algorithm. This fully shows that the HBC algorithm is more competitive in stability, calculation accuracy, and speed.

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“…The algorithm was first suggested by Kennedy and Eberhart in 1995 [43] and has been extensively applied by researchers in solving a variety of optimization problems [45]. Some current developments of the PSO algorithm were applied to solve problems in a variety of applications [46][47][48]. The authors in [46] combined an improved PSO algorithm with the continuous high-degree Bezier curve to solve the problem of smooth path planning for mobile robots.…”

Section: Optimization Algorithmmentioning

confidence: 99%

“…In order to tackle the problem of the optimal placement of motion sensors in smart homes and intelligent environments, [47] proposed a combination of the wale optimization algorithm (WOA) and PSO. An inverse kinematics calculation approach based on improved PSO was suggested in [48] for the inverse kinematic operation of general robots.…”

Section: Optimization Algorithmmentioning

confidence: 99%

Optimum Sizing of Photovoltaic-Battery Power Supply for Drone-Based Cellular Networks

Javidsharifi

Arabani

Kerekes

et al. 2021

Drones

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In order to provide Internet access to rural areas and places without a reliable economic electricity grid, self-sustainable drone-based cellular networks have recently been presented. However, the difficulties of power consumption and mission planning lead to the challenge of optimal sizing of the power supply for future cellular telecommunication networks. In order to deal with this challenge, this paper presents an optimal approach for sizing the photovoltaic (PV)-battery power supply for drone-based cellular networks in remote areas. The main objective of the suggested approach is to minimize the total cost, including the capital and operational expenditures. The suggested framework is applied to an off-grid cellular telecommunication network with drone-based base stations that are powered by PV-battery systems-based recharging sites in a rural location. The PV-battery system is optimally designed for three recharging sites with three different power consumption profiles with different peak and cumulative loads. Results show that the optimal design of the PV-battery system is dependent on geographical data, solar irradiation, and ambient temperature, which affect the output power of the PV system, as well as the power consumption profile, which affects the required number of PV panels and battery capacity.

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A General Robot Inverse Kinematics Solution Method Based on Improved PSO Algorithm

Cited by 64 publications

References 24 publications

Inverse Kinematics Solution of 6-DOF Manipulator Based on Multi-Objective Full-Parameter Optimization PSO Algorithm

Inverse Kinematics Solution of 6-DOF Manipulator Based on Multi-Objective Full-Parameter Optimization PSO Algorithm

A hybrid improved BRO algorithm and its application in inverse kinematics of 7R 6DOF robot

Optimum Sizing of Photovoltaic-Battery Power Supply for Drone-Based Cellular Networks

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