Artificial evolution and real robots

Abstract

Artificial evolution as a design methodology allows the relaxation of many of the constraints that have held back conventional methods. It does not require a complete prior analysis and decomposition of the task to be tackled, as human designers require. However, this freedom comes at some cost; there are a whole new set of issues relating to evolution that must be considered. Standard genetic algorithms may not be appropriate for incremental evolution of robot controllers. Species adaptation genetic algorithms, (SAGA) have been developed to meet these special needs. The main cost of an evolutionary approach is the large number of trials that are required. Simulations-especially those involving vision in complex environments, or modeling detailed semiconductor physics—may not be adequate or practical. Examples of evolved robots will be discussed, including a specialized piece of equipment which allows a robot to be tested using simple vision in real time, and what is believed to be the first successful example of an evolved hardware controller for a robot.