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A. Gasparetto, R. Vidoni, D. Pillan , E. Saccavini
Optimal trajectory generator for painting robots
Proc. of the 9th International Conf. on Advanced Manufacturing Systems and Technology AMST '11, Mali Losinj (Croatia), June 16-17 2011, pp.237-248

Abstract: In this attempt, a new approach to automate and improve a robotic painting task process is described. A direct self-learning programming method is usually adopted, i.e. the operator guides the robot manually through a complete spraying cycle. However, in order to avoid this time-consuming procedure, CAD-based or “acquire-compare-recognize” methods have been developed. This paper presents a general technique that avoids the need for manual programming or CAD drawings and allows to obtain an optimal trajectory by using the graph theory and operative research techniques. After image acquisition, a software module called partitioner splits the object into a set of primitives, then the proposed algorithm is run on the graph in order to generate the optimal path. Then, an optimal trajectory is planned by imposing parameters as velocity, acceleration, rotation of the wrist, opening/closing spray gun for every point of the path. The algorithm has been implemented in Matlab™ and Visual Studi - o.Net™ environments, and extensively tested, both in a simulation environment and on a real painting robot.


Area: Robotica

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