1 / 12

Data Fusion of Four ABS Sensors and GPS for an Enhanced Localization of Car-like Vehicles

Wiwat Ruengmee ICS 280 Special Topic in Ubiquitous Computing Ubiquitous Computing for Post-Crisis Logistics 01/26/2006. Data Fusion of Four ABS Sensors and GPS for an Enhanced Localization of Car-like Vehicles. by Philippe Bonnifait, Pascal Bouron, Paul Crubille, and Dominique Meizel.

devaki
Download Presentation

Data Fusion of Four ABS Sensors and GPS for an Enhanced Localization of Car-like Vehicles

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Wiwat Ruengmee ICS 280 Special Topic in Ubiquitous Computing Ubiquitous Computing for Post-Crisis Logistics 01/26/2006 Data Fusion of Four ABS Sensors and GPS for an Enhanced Localization of Car-like Vehicles by Philippe Bonnifait, Pascal Bouron, Paul Crubille, and Dominique Meizel

  2. Motivations / Problems Wide availability of GPS and ABS systems in modern cars. GPS suffers from satellite masks. Classical solutions to satellite masks problem of GPS are an odometer, a gyro, and a magnetic compass. Implement and test the localization system using GPS, ABS sensors, and a driving wheel encoder. Improve the precision due to the redundancy of measurements. Odometry versus Dead Reckoning. This paper presents a new odometric technique and the data fusion using Extended Kalman Filter (EKF) to estimate the localization.

  3. Approach (1) Odometric technique using data from 4 ABS sensors together with a driving wheel encoder. Basics Displacement between two samples How to estimate ∆ and ω? using the steering wheel ψand the distances travelled by each wheel

  4. Approach (2)

  5. Approach (3) Differential odometry estimation and their estimation • Non-linearity leads to use of Extended Kalman Filter (EKF). • Each (5) estimation of (∆, ω) to provide an odometric location is called “odometric EKF.”

  6. Approach (4) Sampling is performed when: Each time a GPS measurement is performed. Each time the car has travelled one meter and the steering angle has changed more than 0.5 degree. Sampling frequency is not constant and higher than 1 Hz

  7. Results of the Odometric EKF

  8. Architecture of localization system GPS “1PPS” signal (x, y) (x, y, Φ) P ABS Computer + Steering Angle Odometric EKF Localiser EKF ζ S v ζ = An estimation S = Covariance matrix

  9. Results of Sensor Fusion Of GPS and Odemetry Experiments: 9.6 km long course Three characteristics: normal operation seven small GPS masks of ten seconds Large masks of 5 minutes Use of all the ABS sensors increases the precision of the positioning system.

  10. Results of Sensor Fusion Of GPS and Odometry

  11. Results of Sensor Fusion Of GPS and Odometry

  12. Question?

More Related