Non-Line-Of-Sight Error Mitigation For Ultrasonic Positioning System Using LiDAR
Term
4. semester
Education
Publication year
2022
Submitted on
2022-06-01
Pages
8
Abstract
Localisation methods often fuse measurements from both proprioceptive and exteroceptive sensors. Such exteroceptive sensors can be used in multilateration by measuring the distance to pre-installed beacons; however, these position estimates can be biased due to Non-Line-of-Sight (NLoS) errors, caused by an occlusion between receiver and beacon, resulting in the measured Time of Arrival increasing, elongating distance measurement. This paper proposes a method to NLoS identification and mitigation, where a robot’s position estimate is obtained using an Extended Kalman Filter (EKF), which fuses IMU data with distance measurements from an Ultrasonic Beacon System. The NLoS detection is done using LiDAR measurements, to compare the position of the detected surroundings with the position of the currently measured beacon; if the object is detected to be on a direct path between the LiDAR and current beacon, the needed occlusion height is calculated and compared to a Workspace Height Model (WHM). Subsequently, if NLoS is detected, the R-value in the EKF decreases, so the distance measurement from the occluded beacon is weighted less. The system is tested in a manufacturing laboratory, where the results for the NLoS scenario with a LiDAR-augmented EKF is compared to a baseline EKF position estimator. The results show no significant difference between the two mentioned methods.
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