Biological Inspirations in Artificial Intelligence and Robotics

Abstract

In the last two decades, researchers have been more interested in finding ways of modeling biological systems to produce solutions to engineering, science, and real life problems. Early examples of these biologically inspired techniques are Genetic Algorithms and Neural Network. These two model helped researchers solve the problems in function optimization, scheduling, transportation, robotics, medicine, reasoning etc. Biological inspiration has two folds: modeling individual intelligence of a living organism (i.e. neural networks) and modeling the behavior of the group of living organisms such as ant, bees, bacteria, and antibodies. Both approaches have been successful in generating new solutions such as bacterial foraging, ant colony optimization, particle swarm optimization etc. These techniques are mostly used in science and engineering. The area of robotics has many hard problems which these biologically inspired algorithms can help. Robot navigation using Neural networks and Fuzzy Logic is just one example for the success of these algorithms in robotics. Biological inspiration is also helpful in developing new robotic hardware such as insect-like robots, crawling robots, and bird-like robots.

Biography

Ferat Sahin received his B.Sc. in Electronics and Communications Engineering from Istanbul Technical University, Turkey, in 1992. He received his M.Sc. and Ph.D. in Electrical Engineering from Virginia Polytechnic Institute and State University in 1997 and 2000, respectively. His thesis included a Radial Basis Functions Networks solution to a real-time color image classification problem. During his Ph.D., he performed research in biological decision-theoretic intelligent agent design and its application on mobile robots in the context of distributed multi-agent systems. In September 2000, he joined Rochester Institute of Technology, where he works as an associate Professor. His current fields of interests are mobile robots, autonomous robots, modular micro robots, MEMS-based microrobots, swarm intelligence, intelligent control, nonlinear control, multi-agent systems, decision theory, distributed computing, and artificial immune systems. He is a member of the IEEE Systems, Man, and Cybernetics Society, Robotics and Automation Society, Computer Society, and the American Association for Engineering Education (ASEE). He has served as the student activities chair for IEEE SMC society between 2001 and 2003. He is currently the Secretary of the IEEE Systems, Man, and Cybernetics Society. He also volunteers in local IEEE activities. He served as the vice-chair of the IEEE Rochester section between 2003 and 2005.