Open AccessApplication of Improved Ant Colony Algorithm in Mobile Robot Path Planning
Author(s) -
Ming Li,
Lei Wang,
Jingcao Cai
Publication year - 2017
Publication title -
destech transactions on engineering and technology research
Language(s) - English
Resource type - Journals
ISSN - 2475-885X
DOI - 10.12783/dtetr/mdm2016/4879
Subject(s) - ant colony optimization algorithms , motion planning , path (computing) , computer science , mobile robot , ant colony , mathematical optimization , robot , algorithm , artificial intelligence , mathematics , programming language
In order to deal with the problem such as slow convergent speed and local optimum existing in traditional ant colony algorithm (ACO) for mobile robot path planning, an improved ant colony algorithm is proposed, and the improvement includes state transition probability and dynamic pheromone evaporation coefficient. Simulation results show that this method is superior to the traditional ant colony algorithm, and therefore it can effectively improve the quality of the path planning of the robot.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom