Path planning for coal mine robot via improved ant colony optimization algorithm
Baoye Song, Huimin Miao, Lin Xu
Abstract
This paper is concerned with the path planning of the coal mine robot. A new workspace model is presented to describe the complex coal mine environment. Thus, the cost of a path is composed of not only the distance of the path but also some hybrid costs that can be linked to the criteria of path optimization. To overcome the drawbacks of conventional ant colony optimization (ACO) algorithm, an improved ACO algorithm is developed to tackle the issues of path planning of coal mine robot based on the new workspace model. Some simulation experiments are carried out on the path planning of coal mine robot, and the validity and superiority of the new approach can be confirmed by the simulation results.
Topics & Concepts
Ant colony optimization algorithmsCoal miningMotion planningPath (computing)WorkspaceRobotMathematical optimizationEngineeringComputer scienceAlgorithmCoalArtificial intelligenceMathematicsWaste managementProgramming languageRobotic Path Planning AlgorithmsBelt Conveyor Systems EngineeringPower Line Inspection Robots