Title :
A 3D pose estimator for the visually impaired
Author :
Hesch, Joel A. ; Mirzaei, Faraz M. ; Mariottini, Gian Luca ; Roumeliotis, Stergios I.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of Minnesota, Minneapolis, MN, USA
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 realtime indoor localization.
Keywords :
Kalman filters; handicapped aids; nonlinear filters; optical scanners; pose estimation; 2D laser scanner; 3D pose estimator; 3D structural planes; Lie derivatives; extended Kalman filter; indoor localization system; inertial measurement unit; orientation estimation; six degree-of-freedom; Buildings; Gyroscopes; Intelligent robots; Laser theory; Measurement units; Navigation; Packaging; Sensor systems; USA Councils; Velocity measurement;
Conference_Titel :
Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-3803-7
Electronic_ISBN :
978-1-4244-3804-4
DOI :
10.1109/IROS.2009.5354060