The Mini-Robot Khepera as a Foraging Animate: Synthesis and Analysis of Behaviour

Abstract

The work presented in this paper deals with the development of a methodology\nfor resource-efficient behaviour synthesis on autonomous systems. In this context, a definition\nof a maximal problem with respect to the resources of a given system is introduced. It\nis elucidated by means of an exemplary implementation of the solution to such a problem\nusing the mini-robot Khepera as the experimental platform. The described task consists of\nexploring an unknown and dynamically changing environment, collecting and transporting\nobjects, which are associated with light-sources, and navigating to a home-base. The critical\npoint is represented by the accumulated positioning errors in odometrical path-integration\ndue to slippage. Therefore, adaptive sensor calibration using a specific variant of Kohonen’s\nalgorithm is applied in two cases to extract symbolic, e.g. geometric, information from the\nsub-symbolic sensor data, which is used to enhance position control by landmark mapping\nand orientation. In order to successfully handle the arising complex interactions, a heterogeneous\ncontrol-architecture based on a parallel implementation of basic behaviours coupled\nby a rule-based central unit is proposed.