The Ant Algorithm for Solving Robot Path Planning Problem

Authors:
Gengqian Liu;Yuqing Peng;Xiangdan Hou
Affiliations:
Hebei University of Technology;Hebei University of Technology;Hebei University of Technology
Venue:
ICITA '05 Proceedings of the Third International Conference on Information Technology and Applications (ICITA'05) Volume 2 - Volume 02
Year:
2005

Citing 0
Cited 7

Study on adaptive planning strategy using ant colony algorithm based on predictive learning

CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
A new mobile robot navigation method using fuzzy logic and a modified Q-learning algorithm

Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Comparative study of genetic algorithm and ant colony optimization algorithm performances for robot path planning in global static environments of different complexities

CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
A Novel Immune Network Strategy for Robot Path Planning in Complicated Environments

Journal of Intelligent and Robotic Systems
Hybrid ant colony and immune network algorithm based on improved apf for optimal motion planning

Robotica
Ant colony system for robot path planning in global static environment

ICOSSSE'10 Proceedings of the 9th WSEAS international conference on System science and simulation in engineering
A focused wave front algorithm for mobile robot path planning

HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

Using ant algorithm, robot path planning in two-dimension environment is studied. It introduces the intelligent finding optimum mechanism of ant colony. It solves the drawback of local optimization and expedites searching speed. The mathematical model is established and the algorithm is achieved with VB language, the result shows it is valid with the capability of robust and extensibility.