Multi-objective Trajectory Planning Method based on the Improved Elitist Non-dominated Sorting Genetic Algorithm

Wang, Zesheng; Li, Yanbiao; Shuai, Kun; Zhu, Wentao; Chen, Bin; Chen, Ke

doi:10.1186/s10033-021-00669-x

Cited by 22 publications

(6 citation statements)

References 37 publications

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“…The mount path plan in this article belongs to a discrete type problem, where the position of the particles represents the mount order of three robots, and the velocity of the particles represents the exchange sequence, changing the position of the particles [32]. The speed is composed of several arrays, each containing two mount position numbers to be exchanged.…”

Section: Improved Pso Algorithmmentioning

confidence: 99%

Path Planning for Mount Robot Based on Improved Particle Swarm Optimization Algorithm

Li,

Tian,

Hou

et al. 2023

Electronics

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To address the problem of cooperative work among right-angle coordinate robots in spacecraft structural plate mount tasks, an improved particle swarm optimization (PSO) algorithm was proposed to assign paths to three robots in a surface-mounted technology (SMT) machine. First, the optimization objective of path planning was established by analyzing the working process of the SMT machine. Then, the inertia weight update strategy was designed to overcome the early convergence of the traditional PSO algorithm, and the learning factor of each particle was calculated using fuzzy control to improve the global search capability. To deal with the concentration phenomenon of particles in the iterative process, the genetic algorithm (GA) was introduced when the particles were similar. The particles were divided into elite, high-quality, or low-quality particles according to their performance. New particles were generated through selection and crossover operations to maintain the particle diversity. The performance of the proposed algorithm was verified with the simulation results, which could shorten the planning path and quicken the convergence compared to the traditional PSO or GA. For large and complex maps, the proposed algorithm shortens the path by 7.49% and 11.49% compared to traditional PSO algorithms, and by 3.98% and 4.02% compared to GA.

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Section: Improved Pso Algorithmmentioning

confidence: 99%

Path Planning for Mount Robot Based on Improved Particle Swarm Optimization Algorithm

Li,

Tian,

Hou

et al. 2023

Electronics

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“…The trajectory function is composed of a quintic polynomial and a cubic Bezier curve, and then three genetic operators are introduced: sorting group selection, direction-based crossover and mutation with adaptive precision control. The optimal solution of the algorithm is determined through fuzzy comprehensive evaluation to obtain the optimal trajectory [12]. Huang et al (2022) proposed an adaptive optics technique based on genetic algorithm to detect the twisted wavefront of a laser beam, and then perform aberration correction, which has optimized the performance of two-photon fluorescence microscopy.…”

Section: Related Workmentioning

confidence: 99%

Research on the Optimization Problem of Agricultural Product Logistics based on Genetic Algorithm

Wang¹

2022

IJACSA

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China's national development and reform commission issued the "logistics industry adjustment and revitalization plan" in 2009 to support the development of agricultural product logistics and distribution centers. China's agricultural product logistics and distribution have entered a stage of rapid development. With the rise of the sharing economy, logistics has become a bottleneck restricting the further development of agricultural product distribution. In order to realize the effective cooperation among the main body of agricultural product logistics distribution, improve the distribution efficiency and reduce the distribution cost, a logistics distribution optimization model based on the two-layer planning idea and genetic algorithm is proposed. A two-level programming model is constructed by combining qualitative and quantitative methods, theory and examples, and insertion and deletion operators are introduced to optimize the genetic algorithm. The research results show that the optimized genetic algorithm has a 54.55% increase in convergence speed, 1.08% in performance, and a 54.231% reduction in path length compared to the benchmark algorithm. It effectively improves the efficiency of path planning and saves the planning cost, and the final target value is reduced by 48.19%.

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“…Then, the most suitable solution is selected using the normalized weighting function. A novel optimal trajectory planning method was constructed by Wang et al [12]. A trajectory was created with fifth-order polynomials and cubic Bézier curves.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Objective Trajectory Planning Method of the Dual-Arm Robot for Cabin Docking Based on the Modified Cuckoo Search Algorithm

Liu,

Pan

2024

Machines

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During the assembly of mechanical systems, the dual-arm robot is always used for cabin docking. In order to ensure the accuracy and reliability of cabin docking, a multi-objective trajectory planning method for the dual-arm robot was proposed. A kinematic model of the dual-arm robot was constructed based on the Denavit–Hartenberg (D-H) method firstly. Then, in the Cartesian space, the end trajectory of the dual-arm robot was confirmed by the fifth-order B-spline curve. On the basis of a traditional multi-objective cuckoo search algorithm, a modified cuckoo algorithm was built using the improved initial population generation method and the step size. The total consumption time and joint impact were selected as the objective functions, the overall optimal solution for the modified cuckoo algorithm was obtained using the normalized evaluation method. The optimal trajectory planning was achieved. Finally, the feasibility and effectiveness of the trajectory planning method were verified with the experiments.

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Multi-objective Trajectory Planning Method based on the Improved Elitist Non-dominated Sorting Genetic Algorithm

Cited by 22 publications

References 37 publications

Path Planning for Mount Robot Based on Improved Particle Swarm Optimization Algorithm

Path Planning for Mount Robot Based on Improved Particle Swarm Optimization Algorithm

Research on the Optimization Problem of Agricultural Product Logistics based on Genetic Algorithm

A Multi-Objective Trajectory Planning Method of the Dual-Arm Robot for Cabin Docking Based on the Modified Cuckoo Search Algorithm

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