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Enhancement of Ant Colony Optimization in Multi-Robot Source Seeking Coordination

Jun Wei Lee, Nyiak Tien Tang, Kit Guan Lim, Min Keng Tan, Baojian Yang, Kenneth Tze Kin Teo

发表年份
2019
引用次数
6

摘要

This research presents dynamic approaches for swarm robotics system and subsequently achieve enhanced strategies to enhance equilibrium and optimize power usage. Method apply in progress of the project can be divided into hardware platform, control and optimization, and lastly measurement and analysis method. In hardware platform, the speed of rotation of the wheel is controlled for various movement such as direct motion and rotation in place. Optimization method is focused on ant colony optimization. The corrected equation for robot localization control provides more precise mathematical model for manipulating the robot motion. This research compared ACO, dynamic ACO and Dijkstra algorithm in simulated static condition. The result shows that Standard ACO outperforms others algorithm in static condition while Improved algorithm is best used in dynamic conditions.

关键词

Ant colony optimization algorithmsComputer scienceRobotArtificial intelligenceRoboticsRotation (mathematics)Dijkstra's algorithmSwarm roboticsMotion controlMathematical optimization

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