An evolution standing on the design of redundant manipulators

Abstract

The dynamic behaviour of robot manipulators is complex. So complex that classical optimization methodologies are unable to optimize their performance. Thus, though improved performance would yield high financial rewards, industrial robots exhibit sub-optimal performance. It is generally accepted that it is the mechanical design of manipulators — the morphology of the articulate arm — which is the bottleneck element impairing robot utility. This is due to design methodologies being too rigid and inflexible to offer novel design concepts. Furthermore, in spite of their supremacy, highly redundant structures are not being utilized because these structures are evermore complex to design and control with to date technology.

This paper suggests that improved manipulator design can be achieved through the application of a genetic algorithm. Initially, the genetic algorithm is applied to the morphology optimization of three-link, revolute planar robot manipulator, but the model is not restricted to the amount of redundancy it considers. It is further suggested, that the use of a genetic algorithm as a design tool, is particularly effective when considering structures which incorporate extensive redundancy.