Robot Path Planning of Improved Adaptive Ant Colony System Algorithm Based on Dijkstra

Path planning is one of the key technologies of robot. Aiming at the problems of slow convergence speed and inefficient search of traditional Ant Colony System Algorithm, an adaptive Ant Colony System Algorithm based on Dijkstra is proposed in the paper. Firstly, Dijkstra algorithm is applied to sea...

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Published inJournal of Robotics Vol. 2022; pp. 1 - 11
Main Authors Gu, Chonglin, Feng, Ansong, Wang, Guozhan, Liu, Xiqing
Format Journal Article
LanguageEnglish
Published New York Hindawi 15.12.2022
John Wiley & Sons, Inc
Wiley
Subjects
Adaptive algorithms
Algorithms
Ant colony optimization
Convergence
Dijkstra's algorithm
Heuristic
Intelligence
Interpolation
Optimization algorithms
Path planning
Pheromones
Planning
Pseudorandom
Robots
Searching
Simulation methods
Transition probabilities
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Abstract Path planning is one of the key technologies of robot. Aiming at the problems of slow convergence speed and inefficient search of traditional Ant Colony System Algorithm, an adaptive Ant Colony System Algorithm based on Dijkstra is proposed in the paper. Firstly, Dijkstra algorithm is applied to searching the initial path in the grid environment, constructing the initial path, optimizing the initial pheromone in the region, therefore, the Ant Colony System Algorithm avoid falling into blind search in the initial stage; In the transition probability, the disguised angle probability function and parameter adaptive pseudo-random proportion rule are introduced to improve the search efficiency and convergence speed of the algorithm, and eliminate the inferior ant path; Finally, B-spline interpolation curve is used to smooth the path. Compared with the traditional Ant Colony System Algorithm, the simulation results in the grid environment demonstrating its effectiveness to improve convergence speed and to enhance search efficiency are provided. The characteristics of the improved Ant Colony System Algorithm are faster convergence speed and better planning.
AbstractList Path planning is one of the key technologies of robot. Aiming at the problems of slow convergence speed and inefficient search of traditional Ant Colony System Algorithm, an adaptive Ant Colony System Algorithm based on Dijkstra is proposed in the paper. Firstly, Dijkstra algorithm is applied to searching the initial path in the grid environment, constructing the initial path, optimizing the initial pheromone in the region, therefore, the Ant Colony System Algorithm avoid falling into blind search in the initial stage; In the transition probability, the disguised angle probability function and parameter adaptive pseudo-random proportion rule are introduced to improve the search efficiency and convergence speed of the algorithm, and eliminate the inferior ant path; Finally, B-spline interpolation curve is used to smooth the path. Compared with the traditional Ant Colony System Algorithm, the simulation results in the grid environment demonstrating its effectiveness to improve convergence speed and to enhance search efficiency are provided. The characteristics of the improved Ant Colony System Algorithm are faster convergence speed and better planning.
Audience Academic
Author Feng, Ansong
Wang, Guozhan
Liu, Xiqing
Gu, Chonglin
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SubjectTerms Adaptive algorithms
Algorithms
Ant colony optimization
Convergence
Dijkstra's algorithm
Heuristic
Intelligence
Interpolation
Optimization algorithms
Path planning
Pheromones
Planning
Pseudorandom
Robots
Searching
Simulation methods
Transition probabilities
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Title Robot Path Planning of Improved Adaptive Ant Colony System Algorithm Based on Dijkstra
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