TY - GEN
T1 - Indoor Position Estimation Using NLoS Reflected Path with Wireless Distance Sensors
AU - Itsuka, Tomoya
AU - Kurazume, Ryo
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024/10/14
Y1 - 2024/10/14
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85216490681&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85216490681&partnerID=8YFLogxK
U2 - 10.1109/IROS58592.2024.10802063
DO - 10.1109/IROS58592.2024.10802063
M3 - Conference contribution
AN - SCOPUS:85216490681
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 5573
EP - 5580
BT - 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2024
Y2 - 14 October 2024 through 18 October 2024
ER -