This paper investigates a closed-loop visual servo control scheme for controlling the position of a fully constrained cable-driven parallel robot (CDPR) designed for functional rehabilitation tasks. The control system incorporates real-time position correction using an Intel RealSense camera. Our CDPR features four cables exiting from pulleys, driven by AC servomotors, to move the moving platform (MP). The focus of this work is the development of a control scheme for a closed-loop visual servoing system utilizing depth/RGB images. The developed algorithm uses this data to determine the actual Cartesian position of the MP, which is then compared to the desired position to calculate the required Cartesian displacement. This displacement is fed into the inverse kinematic model to generate the servomotor commands. Three types of trajectories (circular, square, and triangular) are used to test the controller’s compliance with its position. Compared to the open-loop control of the robot, the new control system increases positional accuracy and effectively handles cable behavior, various perturbations, and modeling errors. The obtained results showed significant improvements in control performance, notably reduced root mean square error and maximal error in terms of position.

Virtual Reality (VR) is progressively adopted at different stages of design and product development. Consequently, evolving interaction requirements in engineering design and development for VR are essential for technology adoption. One of these requirements is real-time positional tracking. This paper aims to present an experimental design of a new real-time positional tracking device (tracker), that is more compact than the existing solution, while addressing factors such as wearability and connectivity. We compare the simulation of the proposed device and the existing solution, discuss the results, and the limitations. The new experimental shape of the device is tailored towards research, allowing the engineering designer to take advantage of a new tracker alternative in new ways, and opens the door to new VR applications in research and product development.

Impairment of left ventricular contractility due tocardiovascular diseases is reflected in left ventricle (LV) motionpatterns. An abnormal change of torsion or long axis shortening LVvalues can help with the diagnosis and follow-up of LVdysfunction. Tagged Magnetic Resonance (TMR) is a widely spreadmedical imaging modality that allows estimation of the myocardialtissue local deformation. In this work, we introduce a novelvariational framework for extracting the left ventricle dynamicsfrom TMR sequences. A bi-dimensional representation space of TMRimages given by Gabor filter banks is defined. Tracking of thephases of the Gabor response is combined using a variationalframework which regularizes the deformation field just at areaswhere the Gabor amplitude drops, while restoring the underlyingmotion otherwise. The clinical applicability of the proposedmethod is illustrated by extracting normality models of theventricular torsion from 19 healthy subjects.