Bayesian recursive algorithm for width estimation of freespace for a power wheelchair using stereoscopic cameras.
This paper is concerned with the estimation of freespace based on a Bayesian recursive (BR) algorithm for an autonomous wheelchair using stereoscopic cameras by severely disabled people. A stereo disparity map processed from both the left and right camera images is constructed to generate a 3D point map through a geometric projection algorithm. This is then converted to a 2D distance map for the purpose of freespace estimation. The width of freespace is estimated using a BR algorithm based on uncertainty information and control data. Given the probabilities of this width computed, a possible movement decision is then made for the mobile wheelchair. Experimental results obtained in an indoor environment show the effectiveness of this estimation algorithm.
Nguyen
Thanh H
TH
Faculty of Engineering, University of Technology, Sydney, Broadway, NSW 2007, Australia. thnguyen@eng.uts.edu.au
Nguyen
Jordan S
JS
Nguyen
Hung T
HT
D000465:Algorithms; D001362:Avoidance Learning; D001499:Bayes Theorem; D003199:Computer Systems; D003491:Cybernetics; D006233:Persons with Disabilities / Q000534:rehabilitation*; D004867:Equipment Design; D006801:Humans; D015233:Models, Statistical; D010781:Photography; D015357:Vision Disparity; D014785:Vision, Ocular; D014910:Wheelchairs