REOVIEM is a system that use the potencial of virtual reality (VR) and natural user interfaces (NUI) to offer to patients with multiple sclerosis (MS) an intuitive and motivating way to perform several motor rehabilitation exercise. Moreover, REMOVIEM offer to the therapists a new motor rehabilitation tool that it allows control the rehabilitation process, and evaluate the progress of the patients. On the other hand, REMOVIEM is a low cost system, a feature that it facilitates its integration in the clinical rehabilitation centers.
In this paper, a vision-based system is proposed, using the KINECT sensor (KS), for three-dimensional (3D) trajectory tracking. A target object to track in the 3D space is defined in order to describe its trajectory on a virtual reality environment by an emulated quadrotor unmanned aerial vehicle (UAV). The 3D position vector for the centroid of the target to track is recovered from image processing and information from the depth camera. A color-based object tracking approach is used. A stable fuzzy controller, as well as a LQR controller, for the emulated quadrotor UAV are implemented and compared, where the estimated 3D position of the target is given as reference signal. Important benefits of the proposed object tracking method are its efficiency in the use of the information provided by the KS with a low computational cost for image processing to estimate the target object position and the possibility of improving robustness of the image segmentation by online adjustment of the color filtering parameters. The main contribution of the paper is the use of the estimated position as the reference for the simultaneous control of attitude and translation of a quadrotor from a single controller. Experimental simulation results validate the proposed approach.
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