Active leading through obstacles using ant-colony algorithm

Authors:
Ramin Vatankhah;Shahram Etemadi;Aria Alasty;Gholam-Reza Vossoughi;Mehrdad Boroushaki
Affiliations:
Center of Excellence in Design, Robotics, and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology, Azadi Ave., Tehran, Iran;Department of Mechanical and Aerospace Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran;Center of Excellence in Design, Robotics, and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology, Azadi Ave., Tehran, Iran;Center of Excellence in Design, Robotics, and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology, Azadi Ave., Tehran, Iran;Center of Excellence in Design, Robotics, and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology, Azadi Ave., Tehran, Iran
Venue:
Neurocomputing
Year:
2012

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Abstract

In presence of obstacles, inter-agent pulling actions must be bounded. In this case, to remain connected to the group, the leader-agent (LA) must perform an active leading strategy. In this paper, an active leading algorithm is proposed which monitors the neighborhood of the LA and adjusts its velocity. The algorithm is based on the ant colony optimization (ACO) technique. As a real time optimization package, the ACO algorithm maximizes influence of the LA on the group, leading to fast flocking. Comparison with another optimization method is provided as well. Simulations show that the algorithm is successful and cost effective.