Autonomous Robotic Model Based on Human Endocrine System

Abstract

Robots are being used in industry for quite some time and have evolved into much sophisticated autonomous agents. Now, with the advancement in technology, robots are fast entering daily life. This highlights some important aspects of their use; that is collaboration among robots and human-robot interaction. This thesis concentrates on robotic collaboration and presents a model that is based on human endocrine system. In another area of research, namely Computer Immune System, researchers have used human immune system as the basis for their research model. This led us to look for answer to our problem inside human physiological systems. We chose Blood Glucose Control Mechanism as our source from among other systems because it is simpler and has the characteristics that our robotic collaboration model can be based on. We implemented the model in a hypothetical field of underground mines where two types of robots were used for mine detection and removal. A visual simulation was also developed. The data was then analyzed in terms of average time required to detect and to remove a single mine. We repeated the experiments 5 times, with number of mines varying from 1 through 15, and then calculated the average time. The results show that, as the number of mines increases, the average detection and removal time decreases. The implementation of this model showed that this model may be implemented with real robots. The model is scalable, robust and has no single point of failure. Robots can be added and / or removed while in operation without affecting overall system. This may provide the basis for future work where this model may be implemented with real robots.