Experimental results in range-only localization with radio

We present an early experimental result toward solving the localization problem with range-only sensors. We perform an experiment in which a mobile robot localizes using dead reckoning and range measurements to stationary radio-frequency beacons in its environment, incorporating the range measurements into the position estimate using a Kalman filter. This data set involves over 20,000 range readings to surveyed beacons while a robot moved continuously over a path for nearly 1 hour. Careful groundtruth accurate to a few centimeters was recorded during this motion. We show the improvement of the robot's position estimate over dead reckoning even when the range readings are very noisy. We extend this approach to the problem of simultaneous localization and mapping (SLAM), localizing both the robot and tag positions from noisy initial estimates.