Indoor Position Estimation Using NLoS Reflected Path with Wireless Distance Sensors

Indoor robot localization is important for the realization of autonomous service robots. Various studies have been conducted on "indoor GPS" measurements using wireless distance sensors such as ultrasonic beacons. However, when these beacons encounter non-line-of-sight (NLoS) conditions due to obstacles, accurate distance measurements become challenging because of multipath and other effects. In this study, we propose a method for simultaneously estimating a robot’s position and distance to reflective surfaces in an environment using wireless distance sensors. The proposed method can estimate not only the robot’s position but also the reflection of the beacon signal. First, the wheel odometry of the robot is assumed to be the initial value, and the measured distance from the beacon to the robot is used as a factor to construct the factor graph. Second, the distance to the reflective surface of the beacon signal, which is parallel to the robot’s movement plane, was estimated from the robot position sequence using the GMM and used as a noise model in the factor graph. Finally, the method is evaluated by acquiring data in a real environment with obstacles. Compared with a method that does not consider reflection paths, this method demonstrated improved accuracy and effectiveness.