Paper Info
Title
A 3D pose estimator for the visually impaired
Abstract
This paper presents an indoor localization system for the visually impaired. The basis of our system is an Extended Kalman Filter (EKF) for six degree-of-freedom (d.o.f.) position and orientation (pose) estimation. The sensing platform consists of an Inertial Measurement Unit (IMU) and a 2D laser scanner. The IMU measurements are integrated to obtain pose estimates which are subsequently corrected using line-to-plane correspondences between linear segments in the laser-scan data and known 3D structural planes of the building. Furthermore, we utilize Lie derivatives to show that the system is observable when at least three planes are detected by the laser scanner. Experimental results are presented that demonstrate the reliability of the proposed method for accurate and real-time indoor localization.
Year
DOI
Venue
2009
10.1109/IROS.2009.5354060
St. Louis, MO
Keywords
Field
DocType
extended kalman filter,lie derivative,laser scanner,imu measurement,indoor localization system,laser-scan data,inertial measurement unit,real-time indoor localization,line-to-plane correspondence,kalman filters,gyroscopes,lasers,local system,3d pose estimation,degree of freedom,pose estimation,laser scanning,navigation,accelerometers
Computer vision,Gyroscope,Extended Kalman filter,Laser scanning,Accelerometer,Computer science,Kalman filter,Pose,Inertial measurement unit,Artificial intelligence,Estimator
Conference
ISBN
Citations 
PageRank 
978-1-4244-3804-4
8
0.68
References 
Authors
21
4
Name
Order
Citations
PageRank
Joel A. Hesch127313.62
Faraz M. Mirzaei21458.11
Gian Luca Mariottini322620.53
Stergios I. Roumeliotis42124151.96