TY - GEN
T1 - Poster Abstract: Automatic Calibration of Device Attitude in Inertial Measurement Unit Based Traffic Probe Vehicles
AU - Mousa, Mustafa
AU - Sharma, Kapil
AU - Claudel, Christian
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2016/4/28
Y1 - 2016/4/28
N2 - Probe vehicles consist in mobile traffic sensor networks that evolve with the flow of vehicles, transmitting velocity and position measurements along their path, generated using GPSs. To address the urban positioning issues of GPSs, we propose to replace them with inertial measurement units onboard vehicles, to estimate vehicle location and attitude using inertial data only. While promising, this technology requires one to carefully calibrate the orientation of the device inside the vehicle to be able to process the acceleration and rate gyro data. In this article, we propose a scheme that can perform this calibration automatically by leveraging the kinematic constraints of ground vehicles, and that can be implemented on low-end computational platforms. Preliminary testing shows that the proposed scheme enables one to accurately estimate the actual accelerations and rotation rates in the vehicle coordinates. © 2016 IEEE.
AB - Probe vehicles consist in mobile traffic sensor networks that evolve with the flow of vehicles, transmitting velocity and position measurements along their path, generated using GPSs. To address the urban positioning issues of GPSs, we propose to replace them with inertial measurement units onboard vehicles, to estimate vehicle location and attitude using inertial data only. While promising, this technology requires one to carefully calibrate the orientation of the device inside the vehicle to be able to process the acceleration and rate gyro data. In this article, we propose a scheme that can perform this calibration automatically by leveraging the kinematic constraints of ground vehicles, and that can be implemented on low-end computational platforms. Preliminary testing shows that the proposed scheme enables one to accurately estimate the actual accelerations and rotation rates in the vehicle coordinates. © 2016 IEEE.
UR - http://hdl.handle.net/10754/621286
UR - http://ieeexplore.ieee.org/document/7460698/
UR - http://www.scopus.com/inward/record.url?scp=84971254185&partnerID=8YFLogxK
U2 - 10.1109/IPSN.2016.7460698
DO - 10.1109/IPSN.2016.7460698
M3 - Conference contribution
SN - 9781509008025
BT - 2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -