Indoor navigation system based on omni-directional corridorguidelines

Finding way in indoor environments may pose a challenge to people who have some sort of visual loss. This paper describes straight corridor positioning and junction detection algorithms for use in indoor navigation system which is designed for the visually impaired. Also, a model that extracts the edges from the image captured by omni-camera is proposed and the system can direct the visually impaired according to the edge information so that they can move in correct direction and in the middle of the corridor. The proposed navigation system was carried out using omni-camera which can capture images of 360deg view. It has many advantages compared with the conventional camera. Our experiment results show that it works well in corridor environment.

[1]  Alessandro Saffiotti,et al.  Model-Free Execution Monitoring in Behavior-Based Robotics , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[2]  Steven M. LaValle,et al.  Distance-Optimal Navigation in an Unknown Environment Without Sensing Distances , 2007, IEEE Transactions on Robotics.

[3]  Wen-Hsiang Tsai,et al.  Vision-Based Autonomous Vehicle Guidance in Indoor Environments Using Odometer and House Corner Location Information , 2006, 2006 International Conference on Intelligent Information Hiding and Multimedia.

[4]  José Santos-Victor,et al.  Topological Maps for Visual Navigation , 1999, ICVS.

[5]  J. Samarabandu,et al.  Investigating the Performance of Corridor and Door Detection Algorithms in Different Environments , 2006, 2006 International Conference on Information and Automation.

[6]  Alison K Brown,et al.  Urban/Indoor Navigation Using Network Assisted GPS , 2006 .

[7]  José Santos-Victor,et al.  Vision-based navigation and environmental representations with an omnidirectional camera , 2000, IEEE Trans. Robotics Autom..

[8]  Hisayuki Tatsumi,et al.  Autonomous navigation of RFID-sensing robots - information ensuring for the visually impaired (2) , 2005, 2005 IEEE International Conference on Systems, Man and Cybernetics.

[9]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.