A refined immune systems inspired model for multi-robot shepherding

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.