Application of Improved Ant Colony Algorithm in the Path Planning Problem of Mobile Robot

2019 ◽  
Author(s):  
Min Cao ◽  
Yang Yang ◽  
Lianqing Wang
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Planning Problem ◽  
Path Planning Problem ◽  
Improved Ant Colony Algorithm

scholarly journals An Improved Ant Colony Algorithm for Solving the Path Planning Problem of the Omnidirectional Mobile Vehicle

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Jiang Zhao ◽  
Dingding Cheng ◽  
Chongqing Hao
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Selection Strategy ◽  
Planning Problem ◽  
Evaporation Coefficient ◽  
Mobile Vehicle ◽  
Starting Point ◽  
Path Planning Problem ◽  
Improved Ant Colony Algorithm

This paper presents an improved ant colony algorithm for the path planning of the omnidirectional mobile vehicle. The purpose of the improved ant colony algorithm is to design an appropriate route to connect the starting point and ending point of the environment with obstacles. Ant colony algorithm, which is used to solve the path planning problem, is improved according to the characteristics of the omnidirectional mobile vehicle. And in the improved algorithm, the nonuniform distribution of the initial pheromone and the selection strategy with direction play a very positive role in the path search. The coverage and updating strategy of pheromone is introduced to avoid repeated search reducing the effect of the number of ants on the performance of the algorithm. In addition, the pheromone evaporation coefficient is segmented and adjusted, which can effectively balance the convergence speed and search ability. Finally, this paper provides a theoretical basis for the improved ant colony algorithm by strict mathematical derivation, and some numerical simulations are also given to illustrate the effectiveness of the theoretical results.

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

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wenming Wang ◽  
Jiangdong Zhao ◽  
Zebin Li ◽  
Ji Huang
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Local Optimum ◽  
Planning Problem ◽  
Turning Angle ◽  
Heuristic Information ◽  
Starting Point ◽  
Improved Ant Colony Algorithm

Aiming at the problems of slow convergence, easy to fall into local optimum, and poor smoothness of traditional ant colony algorithm in mobile robot path planning, an improved ant colony algorithm based on path smoothing factor was proposed. Firstly, the environment map was constructed based on the grid method, and each grid was marked to make the ant colony move from the initial grid to the target grid for path search. Then, the heuristic information is improved by referring to the direction information of the starting point and the end point and combining with the turning angle. By improving the heuristic information, the direction of the search is increased and the turning angle of the robot is reduced. Finally, the pheromone updating rules were improved, the smoothness of the two-dimensional path was considered, the turning times of the robot were reduced, and a new path evaluation function was introduced to enhance the pheromone differentiation of the effective path. At the same time, the Max-Min Ant System (MMAS) algorithm was used to limit the pheromone concentration to avoid being trapped in the local optimum path. The simulation results show that the improved ant colony algorithm can search the optimal path length and plan a smoother and safer path with fast convergence speed, which effectively solves the global path planning problem of mobile robot.

An Improved Ant Colony System for Inspection Path Planning Problem and Convergence Analysis

2013 ◽  
Vol 483 ◽  
pp. 611-614
Author(s):  
Wen Bo Wang
Keyword(s):  
Path Planning ◽  
Convergence Analysis ◽  
Ant Colony Algorithm ◽  
Step Function ◽  
Ant Colony ◽  
Ant Colony System ◽  
Planning Problem ◽  
Path Planning Problem

The ant colony algorithm to solve the inspection path planning problem well. The algorithm runs in the different requirements of path and the convergence of the step function q0. The concentration of pheromone bounds, prevent the algorithm premature. To improve the convergence of the proposed algorithm are analyzed and tested by means of experiment.

The Application of an Improved Ant Colony Algorithm in Mobile Robot Path Planning

2011 ◽  
Vol 467-469 ◽  
pp. 222-225 ◽  
Author(s):  
Xiao Guang Zhu ◽  
Qing Yao Han ◽  
Zhang Qi Wang
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Ant Colony Algorithm ◽  
Special Functions ◽  
Grid Method ◽  
Ant Colony ◽  
Robot Path Planning ◽  
Improve Performance ◽  
Improved Ant Colony Algorithm ◽  
Robot Path

This paper presents an improved ant colony algorithm to plan an optimal collision-free path for mobile robot in complicated static environment. Based on the work space model with grid method, simulated foraging behavior of ants and to serve the mobile robot path planning, update the conventional ant colony algorithm with some special functions. To avoid mobile robot path deadlock, a dead-corner table is established and the penalty function is used to update the trail intensity when an ant explores a dead—corner in the path searching. The simulation results show that the algorithm can improve performance of path planning obviously, and the algorithm is simple and effective.

Sign in / Sign up

Export Citation Format

Share Document