JRM Vol.30 No.1 pp. 128-137
doi: 10.20965/jrm.2018.p0128


A New IntelliSense Strategy Based on Artificial Immune System for Multi-Robot Cooperation

Tao Xu, Zengyong Shi, and Xiaomin Li

School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology
Eastern HuaLan Avenue, Xinxiang, Henan 453003, China

May 14, 2017
December 13, 2017
February 20, 2018
intelliSense, artificial immune system, environment exploration, multi-robotic cooperation
A New IntelliSense Strategy Based on Artificial Immune System for Multi-Robot Cooperation

The node decision rule and the final point cloud map results by our method

In this paper, a novel intelliSense strategy based on an artificial immune system for multi-robot cooperation (MRC) is proposed. A laser range finder and camera are mounted on the robot to provide environmental information. Based on the principle of the artificial immune system, environmental information sensed by the robot is considered as an antigen while the robot is regarded as a B-cell and a possible node as an antibody. To improve exploration efficiency, the immune system is utilized in the single robot system (SRS) and multi-robotic system (MRS). Antibody-antigen affinity is calculated to choose optimal number of possible node, ensuring that the exploration path is optimal. Each robot explores independently according to affinity information, and cooperation among robots can be realized by utilizing the interactions among antibodies. In order to make the map merging strategy more persuasive, the Scale-Invariant Feature Transform (SIFT) feature is further used to identify the same region. In a real-context experiment, the proposed algorithm results in more accurate exploration, and it is verified that the proposed intelliSense strategy improves the accuracy and execution efficiency for mobile robots.

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Last updated on Mar. 16, 2018