Artificial muscles are formed by attaching a conducting polymeric film to a non-conducting one. The flow of an electric current produces a macroscopic bending movement on the muscle. A good characterization of both, motion rate and energy of curvature, is required for improving the efficiency of these devices. In this paper, a two-cam stereo vision system is proposed to acquire and process the image sequence and a 3D snake for tracking the muscle. From the curve given by the snake, mechanical parameters of the artificial muscle can be estimated. The movements along the life cycle of the muscle can be compared with the energy consumed in each cycle. This is necessary for determining the span life of these devices in applications where they work as actuators. Results prove the validity of this approach.
Image matching of deformable structures has captured great attention in image processing, and specially in the medical field. This papcr proposes a method that faces the ill-posed nature of this problem, by using a cluster-sized similarity cost function, the ambiguity in each similarity map is described by a fuzzy parametric model, and, finally, a spatially non-uniform fuzzy interpolation is used to translate the parametric info into a set of matching field vectors. The method obtains the spatial matching between the two images in a global spatial extent and with sub-pixel accuracy. Results of the method on real images and high non-rigid artificial deformation proves the validity of the approach. Its extension to B volumetric approach is also suggested.
Artificial muscles are formed by attaching a conducting polymeric film to a non-conducting one. Applying an electrical current on the muscle. a macroscopic bending movement appears on it. Study of curvature variations and related parameters, such as speed of motion or energy of curvature, is necessary for improving the efficiency of these devices. In a previous work. a one-cam computer vision system was developed to estimate motion parameters in 2D with precise results. In this paper, a two-cam stereo vision system is proposed to process the image sequence and track the muscle in 3D. Active contours models are employed in motion detection and mechanical parameters estimation. Results prove the validity of this approach, allowing automatic testing on the research into artificial muscles.
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