  We present Autonomous Rssi based RElative poSitioning and Tracking (ARREST),
a new robotic sensing system for tracking and following a moving, RF-emitting
object, which we refer to as the Leader, solely based on signal strength
information. This kind of system can expand the horizon of autonomous mobile
tracking and distributed robotics into many scenarios with limited visibility
such as nighttime, dense forests, and cluttered environments. Our proposed
tracking agent, which we refer 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 relative position
of the Leader with decimeter level accuracy (which is comparable to a
state-of-the-art 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 (LQG) controller 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 $99\%$
probability in line of sight scenarios, and (2) more than $70\%$ probability in
no line of sight scenarios, when it moves 1.8X faster than the Leader. For
ground truth estimation in real world experiments, we also developed an
integrated TDoA based distance and angle estimation system with centimeter
level localization accuracy in line of sight scenarios. While providing a first
proof of concept, our work opens the door to future research aimed at further
improvements of autonomous RF-based tracking.
