Variational Optical Flow Based Velocity Estimation for Omni-Directional Intelligent Wheelchair

To measure the velocity for the omni-directional intelligent wheelchair for the depth research on control and improve the measured accuracy and computational efficiency, the variational optical flow based velocity estimation method is used in this paper. Firstly, an improved energy functional model which combines a brightness constancy assumption, a gradient constancy assumption, a Laplacian constancy assumption and a discontinuity-preserving spatio-temporal smoothness constraint is employed to improve the accuracy of optical flow estimation; Then, a planar optical flow model based improved voting Random Sample Consensus(RANSAC) method is presented to remove heterogeneous optical flow vectors produced by non-uniform ambient illumination, local motion blur and chaotic surrounding environment. Finally, aiming at the installation attitude of the camera, an effective method of camera attitude adjustment is introduced to simplify the spatial coordinate system transformation and solve the model. This paper has realized the velocity estimation of the wheelchair by real-time acquisition of images in the framework of the Robot Operating System(ROS). Experimental results showed that the wheelchair velocity estimation method performed robustly in the presence of chaotic surrounding environment through the above improvements.