Due to their unique and favorable properties as well as high strength to weight ratio, composite materials are finding increasing applications in automotive, aircraft and other vehicle manufacturing industries. High demand, production rates and increasing part complexity, together with design variations require fast, flexible and fully automated assembly techniques. In automotive and aircraft manufacturing, widely used bonding and sealing processes are automated using industrial robots due to their speed, flexibility and large working volume. However, there are limitations in achieving complete automation of these processes due to the inherent inaccuracies of the industrial robots, workpiece positioning and process tolerances. Currently, the robot programs are generated in CAD/CAM environment and are adjusted manually according to the actual workpiece. An alternate solution is proposed with an on-board vision based sensor setup to adapt the robot path compensating for the robot kinematic inaccuracies, workpiece referencing errors and unique local deformations of the workpiece via a real-time interface. The realized setup consists of a prototype dosing system with two laser line triangulation sensors on the end-effector of a serial robot. The developed real-time application computes the 5 Degrees of Freedom (DOF) deviations and corresponding robot correction signals. The robot executes the generated offline programs for the application process. The implemented “real-time” control scheme adapts the programmed trajectory in accordance with the position, orientation and tolerances of the actual workpiece so that the process tolerances are met.


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    Titel :

    Real-Time Path Correction of an Industrial Robot for Adhesive Application on Composite Structures


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:

    Kongress:

    WCX World Congress Experience ; 2018



    Erscheinungsdatum :

    2018-04-03




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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