원문정보
초록
영어
A variation of Ant Colony System (ACS) is represented in this paper and applied for the Robot Path Planning (RPP) purpose. The algorithm shows a new way to find the shortest path from source to destination in offline mode with the application of in-build path map by following the Robot Path Algorithm (RPA), introduced in this paper. Robot always follow the path map provided to it to find the shortest path as well as it can achieve the knowledge that in which direction, i.e. from one node to the next node, it will have to move. The movement of the robots is based on the movent technique of the ants in the ant colony. Among all the algorithms for finding the shortest path, the proposed Shortest Path Algorithm (SPA), based on Kruskal algorithm, is much more effective and accurate for the RPP problem and will take less computational time and hence increase the efficiency of the work process of the robot system.
목차
1. Introduction
2. Ant Colony System
2.1 Ant behavior
2.2 Algorithm for shortest path
2.3 State transition rule
2.4 Pheromone update rule
3. Robot Colony System (RCS)
3.1 Robot Path Algorithm
3.2 Pseudo code for ACS based RPA
3.3 Robot Path Map (RPM)
3.4 Calculation of Distance
4. Robot Path Map Database
4.1 Shortest path determination algorithm
4.2 Robot Path design and Simulation using Ant Movement
5. Conclusion
Acknowledgments
References