Network centric control for multirobot teams in urban search and rescue

Abstract

Theories from Network-centric Warfare (NCW) distinguish between network-centric and platform-centric orientations to sensing and control. In platform-centric control the operator(s) access and focus on data through platforms they control, a robot's camera, for example. In network-centric control the operator(s) do not access data through platforms but instead through the network without regard to where information originated. The conventional human role in sophisticated information gathering systems is usually as both commander (of platforms) and perceiver. Human sensory and perceptual capabilities, however, far outstrip our abilities to process information frequently making our perceptual function more critical to the mission. The use of human operators as "perceptual sensors" is standard practice for both UAVs and ground robotics where humans are called upon to "process" camera video to find targets and assist in navigation. This paper traces the evolution of an experimental human-multirobot system for Urban Search and Rescue from a platform-centric implementation in which operators navigated robots while searching for victims in streaming video to a network-centric version in which they search recorded video asynchronously. We describe two lines of research leading to our current design. In the first we identify the navigation task as both more difficult and the limiting factor in extending control to larger robot teams. In the second we found a few strategically selected images viewed asynchronously roughly comparable in performance to continuously viewed streaming video.