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

• Published in: Journal of Robotics Vol. 2022; pp. 1 - 11
• Main Authors: Gu, Chonglin, Feng, Ansong, Wang, Guozhan, Liu, Xiqing
• Format: Journal Article
• Language: English
• 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
• ISSN: 1687-9600; 1687-9619
• DOI: 10.1155/2022/9229155

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.