Achieving robust behavior by using proprioceptive activity patterns.

Abstract

This paper proposes a new self-organizing, biologically-inspired control architecture for mobile robots consisting of a controller and a value system. The controller uses activity patterns of visual sensors to determine the motor commands, whereas the value system receives stimuli from proprioceptive sensors. This design decision is justified by the following arguments: (1) the feedback of proprioceptive sensory patterns is omnipresent in biological systems and has been widely neglected in control systems, (2) both components are significantly decoupled by using different sensory modalities, and (3) proprioceptive sensors operate more reliably and can be used more efficiently than visual sensors, such as pixels in a CCD camera. Practical experiments with the Khepera robot show that by using proprioceptive sensor values, the control architecture can adapt to different environments and yield very robust behavior with respect to, for example, sensor failures. Furthermore, the new control architecture can be easily enhanced by further components.