A 3D pose estimator for the visually impaired

Authors:
Joel A. Hesch;Faraz M. Mirzaei;Gian Luca Mariottini;Stergios I. Roumeliotis
Affiliations:
Dept. of Computer Science and Engineering, University of Minnesota;Dept. of Computer Science and Engineering, University of Minnesota;Dept. of Computer Science and Engineering, University of Minnesota;Dept. of Computer Science and Engineering, University of Minnesota
Venue:
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Year:
2009

Citing 14
Cited 3

Pose Determination from Line-to-Plane Correspondences: Existence Condition and Closed-Form Solutions

IEEE Transactions on Pattern Analysis and Machine Intelligence
Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans

Journal of Intelligent and Robotic Systems
Finding Location Using Omnidirectional Video On A Wearable Computing Platform

ISWC '00 Proceedings of the 4th IEEE International Symposium on Wearable Computers
A Wearable Haptic Navigation Guidance System

ISWC '98 Proceedings of the 2nd IEEE International Symposium on Wearable Computers
Drishti: An Integrated Indoor/Outdoor Blind Navigation System and Service

PERCOM '04 Proceedings of the Second IEEE International Conference on Pervasive Computing and Communications (PerCom'04)
Design and development of an indoor navigation and object identification system for the blind

Assets '04 Proceedings of the 6th international ACM SIGACCESS conference on Computers and accessibility
Dynamic Environment Exploration Using a Virtual White Cane

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Digital Sign System for Indoor Wayfinding for the Visually Impaired

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
A Multi-Camera Pose Tracker for Assisting the Visually Impaired

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
A comparison of line extraction algorithms using 2D range data for indoor mobile robotics

Autonomous Robots
SC-KF Mobile Robot Localization: A Stochastic Cloning Kalman Filter for Processing Relative-State Measurements

IEEE Transactions on Robotics
A Kalman Filter-Based Algorithm for IMU-Camera Calibration: Observability Analysis and Performance Evaluation

IEEE Transactions on Robotics
Auditory guidance with the Navbelt-a computerized travel aid forthe blind

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
The GuideCane-applying mobile robot technologies to assist thevisually impaired

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans

Opportunistic strategies for lightweight signal processing for body sensor networks

Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments
The user as a sensor: navigating users with visual impairments in indoor spaces using tactile landmarks

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Integrated online localization and navigation for people with visual impairments using smart phones

ACM Transactions on Interactive Intelligent Systems (TiiS)

Quantified Score

Hi-index	0.00

Visualization

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.