Smooth Path Planning of Mobile Robot Based on Improved Ant Colony Algorithm

Wang, Wenming; Zhao, Jiangdong; Li, Zebin; Huang, Jian

doi:10.1155/2021/4109821

Cited by 11 publications

(6 citation statements)

References 32 publications

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“…In addition, Dijkstra algorithm needs all the distances from the origin to the nodes, and this algorithm will lead to a longer time consumption and a larger memory occupied by the computation. Hence, the algorithm is also not suitable for dealing with map information that is too large or too complex [7].…”

Section: Advantages and Disadvantages Of Dijkstra Algorithmmentioning

confidence: 99%

Dijkstra and A* algorithms in automated vehicle driving

Lin

2024

International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023)

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Path planning technology is one of the current hotspots of research in many intelligent technology fields, which has a broad application prospect and research value. With the rapid improvement of computer arithmetic power and the widespread popularization of automation, automatic driving has gradually become a hot topic of people's attention. Among them, path planning algorithms play a central role in the field of automatic driving. In this paper, firstly, it will summarize and introduce the development history and basic principles of the two basic path algorithms, Dijkstra algorithm and A* algorithm, list the advantages and disadvantages of these two path planning methods based on graph search and the application scenarios, and then analyze and compare Dijkstra algorithm and A* algorithm, discuss their advantages and disadvantages in the field of intelligent driving, and finally make an outlook of future development directions of the path planning technology in the field of intelligent driving. The research in this paper will provide certain reference value to the researchers of path planning algorithms for intelligent vehicles. It will be of great value to the research and application of new path planning algorithms based on Dijkstra and A* algorithms in the future.

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Section: Advantages and Disadvantages Of Dijkstra Algorithmmentioning

confidence: 99%

Dijkstra and A* algorithms in automated vehicle driving

Lin

2024

International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023)

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“…Its positive feedback and synergy make it suitable for use in distributed systems, and its implicit parallelism offers strong development potential. The problems that it can solve have gradually expanded to include some constrained problems and multi-objective problems [15][16][17]. When the ant colony algorithm was initially proposed, it was used for discrete domain optimization problems.…”

Section: Ant Colony Algorithm and Optimizationmentioning

confidence: 99%

Multi-Objective Optimal Design of μ–Controller for Active Magnetic Bearing in High-Speed Motor

Zhu

2023

Actuators

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In this paper, a control strategy based on the inverse system decoupling method and μ-synthesis is proposed to control vibration in a rigid rotor system with active magnetic bearings that are built into high-speed motors. First, the decoupling method is used to decouple the four-degrees-of-freedom state equation of the electromagnetic bearing rigid rotor system; the strongly coupled and nonlinear rotor system is thus decoupled into four independent subsystems, and the eigenvalues of the subsystems are then configured. The uncertain parametric perturbation method is used to model the subsystem, and the multi-objective ant colony algorithm is then used to optimize the sensitivity function and the pole positions to obtain the optimal μ-controller. The closed-loop system thus has the fastest possible response, the strongest internal stability, and the best disturbance rejection capability. Then, the unbalanced force compensation algorithm is used to compensate for the high-frequency eccentric vibration; this algorithm can attenuate the unbalanced eccentric vibration of the rotor to the greatest extent and improve the robust stability of the rotor system. Finally, simulations and experiments show that the proposed control strategy can allow the rotor to be suspended stably and suppress its low-frequency and high-frequency vibrations effectively, providing excellent internal and external stability.

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“…Worst in the traditional algorithm, the ant algorithm of pheromone after positive feedback can lead to search into the local optimal solution. The paper uses the wolves law, pheromone update in a loop, finds a local optimal path and the local path of the worst ants respectively to avoid this problem and reduce the amount of released pheromone concentration [8] . The pheromone concentration of each path is updated according to Equations (8-10).…”

Section: Improved Pheromone Updatementioning

confidence: 99%

Research on vehicle routing planning based on ant colony algorithm

Peng

Shi²,

Liu³

2023

Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022)

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An enhanced ant colony method for omnidirectional mobile vehicle path planning is presented in this paper. The enhanced ant colony algorithm seeks a suitable path that connects the starting and ending sites of the environment while avoiding hazards. The path planning issue, which has been improved to take into consideration the properties of the omnidirectional mobile vehicle, is solved using the ant colony algorithm. Additionally, in the updated approach, the path search is greatly aided by the non-uniform distribution of the initial pheromone and the selection technique with the direction. In order to avoid repetitive searches and reduce the effect of the ant population on the algorithm's performance, the coverage and updating strategy of pheromone is introduced. Furthermore, segmentation and pheromone evaporation coefficient adjustments may be beneficial in achieving a compromise between convergence speed and search capability. This paper's strong mathematical derivation theoretically supports the improved ant colony algorithm, and some numerical simulations are also given to show the effectiveness of the theoretical findings.

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Smooth Path Planning of Mobile Robot Based on Improved Ant Colony Algorithm

Cited by 11 publications

References 32 publications

Dijkstra and A* algorithms in automated vehicle driving

Dijkstra and A* algorithms in automated vehicle driving

Multi-Objective Optimal Design of μ–Controller for Active Magnetic Bearing in High-Speed Motor

Research on vehicle routing planning based on ant colony algorithm

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