A universally manipulable body model: Application of the MMC principle to a dual quaternion representation

Internal models are assumed to be a prerequisite for getting cognitive. In this article, I introduce a neural network approach for a model representing the kinematics of a complex manipulator which at the same time can be used for solving inverse and forward kinematic function. The Mean of Multiple Computation principle applied to a dual quaternion representation of transformations describing the manipulator is extendable to integrate into the model additional sensory information or information concerning the environment. It will be discussed how the body model presented may serve functions related to specific behaviours like targeted movements. But the model is suited to be applied in a more universal way. It can be used for planning ahead in a form of mental simulation for predictive purposes. The principle proposed can be applied to arbitrarily complex geometrical structures.