ARREST: A RSSI Based Approach for Mobile Sensing and Tracking of a Moving Object

Abstract

We present Autonomous Rssi based RElative poSitioning and Tracking (ARREST), a new system for dynamic tracking of moving, RF-emitting object, referred to as the Leader, by a tracking robot that solely employs radio strength measurements. Our proposed tracking agent, referred to as the TrackBot, uses a single rotating, off-the-shelf, directional antenna, novel angle and relative speed estimation algorithms, and Kalman filtering to continually estimate the Leader's relative position with decimeter level accuracy (which is comparable to a multiple access point based RF-localization system) and the relative speed of the Leader with accuracy on the order of 1 m/s. The TrackBot feeds the relative position and speed estimates into a Linear Quadratic Gaussian controller (LQG) to generate a set of control outputs to control the orientation and the movement of the TrackBot. We perform an extensive set of real world experiments with a full-fledged prototype to demonstrate that the TrackBot is able to stay within 5m of the Leader with: (1) more than 99 percent probability in line of sight scenarios, and (2) more than 70 percent probability in no line of sight scenarios, when it moves 1.8X faster than the Leader.