A Refined Immune Systems Inspired Model for Multi-Robot Shepherding

• Main Authors: Razali, Sazalinsyah, Meng, Qinggang, Yang, Shuang-Hua
• Format: Conference or Workshop Item
• Language: English
• Published: 2010
• Subjects: Q Science (General); QA75 Electronic computers. Computer science; QR180 Immunology
• Online Access: http://eprints.utem.edu.my/id/eprint/181/1/razali2010-NaBIC-refined.pdf; http://eprints.utem.edu.my/id/eprint/181/; http://dx.doi.org/10.1109/NABIC.2010.5716358

In this paper, basic biological immune systems and their responses to external elements to maintain an organism's health state are described. The relationship between immune systems and multi-robot systems are also discussed. The proposed algorithm is based on immune network theories that have many similarities with the multi-robot systems domain. The paper describes a refinement of the memory-based immune network that enhances a robot's action-selection process. The refined model; which is based on the Immune Network T-cell-regulated - with Memory (INT-M) model; is applied onto the dog and sheep scenario. The refinements involves the low-level behaviors of the robot dogs, namely Shepherds' Formation and Shepherds' Approach. The shepherds would form a line behind the group of sheep and also obey a safe zone of each sheep, thus achieving better control of the flock. Simulation experiments are conducted on the Player/Stage platform.