An Advanced Quantum Optimization Algorithm for Robot Path Planning

Gao, Liming; Liu, Rong; Wang, Fei; Wu, Weizong; Bai, Baoming; Yang, Sa; Li, Yao

doi:10.1142/s0218126620501224

Cited by 24 publications

(12 citation statements)

References 20 publications

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“…A new quantum-inspired evolutionary algorithm proposed for the robot path planning problem is reportedly suitable for solving large scale optimization problems for both complex static and dynamic environments and outperforms conventional genetic algorithms to a considerable degree [103]. Alexandru et al (2020) provides new quantum schemes that speed up several general-purpose numerical optimization methods for minimizing a function 𝑓 ∶ ℝ 𝑛 → ℝ [104].…”

Section: Ranjbar Et Al (mentioning

confidence: 99%

A Brief Review on Mathematical Tools Applicable to Quantum Computing for Modelling and Optimization Problems in Engineering

et al. 2022

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Since its emergence, quantum computing has enabled a wide spectrum of new possibilities and advantages, including its efficiency in accelerating computational processes exponentially. This has directed much research towards completely novel ways of solving a wide variety of engineering problems, especially through describing quantum versions of many mathematical tools such as Fourier and Laplace transforms, differential equations, systems of linear equations, and optimization techniques, among others. Exploration and development in this direction will revolutionize the world of engineering. In this manuscript, we review the state of the art of these emerging techniques from the perspective of quantum computer development and performance optimization, with a focus on the most common mathematical tools that support engineering applications. This review focuses on the application of these mathematical tools to quantum computer development and performance improvement/optimization. It also identifies the challenges and limitations related to the exploitation of quantum computing and outlines the main opportunities for future contributions. This review aims at offering a valuable reference for researchers in fields of engineering that are likely to turn to quantum computing for solutions. Doi: 10.28991/ESJ-2023-07-01-020 Full Text: PDF

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Section: Ranjbar Et Al (mentioning

confidence: 99%

A Brief Review on Mathematical Tools Applicable to Quantum Computing for Modelling and Optimization Problems in Engineering

et al. 2022

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“…The application of robot in various industries is more and more in-depth, which has greatly changed people's production mode and living standard. With the continuous development of science and technology, traditional industrial robots have been difficult to meet people's needs for industrial production and life, and people's demand for robot intelligence is becoming more and more obvious (Chen & Liu, 2019;Gao et al, 2020;Han, 2019;Xue et al, 2018;. In the development of robot intelligence, path planning is a very important research direction, which is also an important development branch of artificial intelligence, with the characteristics of complexity and nonlinearity.…”

Section: Introductionmentioning

confidence: 99%

Research on Robot Path Perception and Optimization Technology Based on Whale Optimization Algorithm

Zan

2022

JCCE

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With the development of modern sensor technology, the automatic movement of robot has become a reality, and improving the path planning performance of robot in dynamic and complex environment is an important development direction of mobile robot intelligence. In this research, based on the idea of hybrid path planning, whale optimization algorithm is introduced combined with computer perception technology to realize the path planning of robot. In order to improve the performance of the traditional whale optimization algorithm, it is optimized and improved by genetic algorithm. Through the performance simulation analysis of the improved whale optimization algorithm, it can be seen that the improved algorithm has better path optimization performance and significantly improved efficiency compared with other traditional algorithms. It can perceive and calculate an optimized path.

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“…In modern intelligent industrial production, the path optimization problem of welding robots has always been an important research object in the field of robotics. Under the requirements of large-scale industrial production tasks, the path judgment of artificial experience is difficult to meet the requirements of production efficiency [1]. ACO optimization should not only consider the obstacle judgment and the shortest path but also analyze the time and energy consumption of the robot in a complex environment [2].…”

Section: Introductionmentioning

confidence: 99%

Path Optimization of Welding Robot Based on Ant Colony and Genetic Algorithm

Zhang¹

2022

Journal of Applied Mathematics

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While the process of intelligent industrial production is accelerating, the application scope of welding robots is also expanding. For the purpose of reducing the work efficiency and time consumption of the welding robot, the ACO is used for the shortest distance and the GA is used for the shortest time fixed-point path trajectory optimization. The application of parameter optimization and random disturbance factor in the ACO increases the global search performance of the algorithm. In the shortest time trajectory optimization, the B-spline curve interpolation method and the GA are combined to carry out the segmental optimization processing. Simulation experiments show that the optimization strategy of ACO can increase the iterative calculation efficiency and path optimization performance of the algorithm. At the same time, the robot with optimized genetic algorithm has smaller fluctuations in joint angle and angular velocity in the simulated welding task, and the optimization algorithm takes 17.6 s less than the traditional particle swarm algorithm and 11 s less than the single A ∗ algorithm. The experiments confirmed the performance of the ACO-GA for the path optimization of the welding robot, and research can provide a scientific path optimization reference for the welding task of the industrial production line.

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An Advanced Quantum Optimization Algorithm for Robot Path Planning

Cited by 24 publications

References 20 publications

A Brief Review on Mathematical Tools Applicable to Quantum Computing for Modelling and Optimization Problems in Engineering

A Brief Review on Mathematical Tools Applicable to Quantum Computing for Modelling and Optimization Problems in Engineering

Research on Robot Path Perception and Optimization Technology Based on Whale Optimization Algorithm

Path Optimization of Welding Robot Based on Ant Colony and Genetic Algorithm

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