Abstract
We investigate the exploitation of linear models of camera-object interaction for an efficient modeling and control of image-based visual servoing systems. The approach includes a method for coping with those representation ambiguities typical of linear interaction models which may affect both planning and control. The implementation of an eye-in-hand servoing system based on affine camera models and using image contours as relevant visual features is described and discussed. The system, including an image planner, a two-dimensional/three-dimensional (2-D/3-D) controller, and a visual analysis module, allows an intuitive specification and execution of relative positioning tasks w.r.t. still or moving rigid objects. Results of real-time experiments with a robotic platform featuring a PUMA manipulator provide a further insight into characteristics and performance of affine visual servoing systems.
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