Mobile Robot Design Based on Ant Colony Algorithm

2014 ◽  
Vol 484-485 ◽  
pp. 1134-1137
Author(s):  
Li Cai ◽  
Hong Xia Wu ◽  
Rong Zhang
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Real Time ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Robot Design ◽  
Simulation Results

This paper proposes a mobile robot design based on ant colony algorithm, aiming at how to achieve the optimization of path planning. Obstacle detecting and avoidance method for mobile robot are implemented with the photoelectric sensors. Then the ant colony algorithm for path planning is introduced and the simulation results in the software show that the method of introducing ant colony algorithm into mobile robot is convenient, feasible. By this means, the optimum problem is well resolved in real-time way during the running of mobile robot.

Wheeled Robot Path Tracking Study Based on IMM Algorithm

2014 ◽  
Vol 1037 ◽  
pp. 228-231
Author(s):  
Li Cai ◽  
Jian Ping Jia
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Real Time ◽  
Path Tracking ◽  
Wheeled Mobile Robot ◽  
Robot Design ◽  
Matlab Software ◽  
Wheeled Robot ◽  
Simulation Results ◽  
Robot Path

This paper proposes a wheeled robot design based on IMM algorithm , aiming at how to achieve the optimization of path planning. Obstacle detecting and avoidance method for mobile robot are implemented with the photoelectric sensors. Then IMM algorithm for path planning is introduced and the simulation results in the MATLAB software show that the method of introducing IMM into mobile robot is convenient. By this means, the path planning is well optimized in real-time way for wheeled mobile robot.

scholarly journals Mobile robot path planning using an improved ant colony optimization

2018 ◽  
Vol 15 (3) ◽  
pp. 172988141877467 ◽  
Author(s):  
Khaled Akka ◽  
Farid Khaber
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Ant Colony Algorithm ◽  
Search Space ◽  
Step Length ◽  
Ant Colony ◽  
Dynamic Adjustment ◽  
Feedback Information ◽  
Intelligent Optimization Algorithm ◽  
Selection Of

Ant colony algorithm is an intelligent optimization algorithm that is widely used in path planning for mobile robot due to its advantages, such as good feedback information, strong robustness and better distributed computing. However, it has some problems such as the slow convergence and the prematurity. This article introduces an improved ant colony algorithm that uses a stimulating probability to help the ant in its selection of the next grid and employs new heuristic information based on the principle of unlimited step length to expand the vision field and to increase the visibility accuracy; and also the improved algorithm adopts new pheromone updating rule and dynamic adjustment of the evaporation rate to accelerate the convergence speed and to enlarge the search space. Simulation results prove that the proposed algorithm overcomes the shortcomings of the conventional algorithms.

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