Integrating active perception with an autonomous robot architecture

Abstract

Abstract Today’s robotics applications require complex, real-time, high-bandwidth sensor systems. Although many such systems have been developed, integrating them into an autonomous agent architecture remains an area of active research. We have integrated an active stereo vision system with an autonomous agent architecture using a system of perceptual memory. Perceptual memory is an important class of memory because it is designed for the ‘behavior-based’ portion of the agent’s architecture, and not the deliberative portion. This memory maintains current and recent task-dependent perceptual information, as well as expectations about the agent’s immediate environment. Our system of perceptual memory is composed of visual primitives from our stereo system, called proximity spaces. Each proximity space represents a virtual fovea or locus of the agent’s attention. As an application, we present a robot that uses our system of perceptual memory and proximity spaces to ‘attend to’ multiple humans in a complex and unstructured indoor environment.