Abstract
This paper presents an approach for depth sensor based detection of target objects and automated generation of trajectories for a robot-aided object scanning process. In general quality management concerning purchased or manufactured products is of central importance. Inspection and verification processes can be very time consuming or require high personnel expenditures which encourages the utilization of automated quality assessment methods. The presented strategy combines the detection of known objects inside the workspace of a robot based on an Iterative Closest Point (ICP) algorithm with trajectory planning and G code generation. For this purpose the workspace around the target object is divided into sub-volumes to identify a set of 3D support points that are the basis of the final scanning path. This method shows promising results in simulation as well as in first tests on a real system.
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Acknowledgments
This work has been supported by the Austrian COMET-K2 program of the Linz Center of Mechatronics (LCM).
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Ziegler, J., Gattringer, H., Kaserer, D., Müller, A. (2018). Automated, Depth Sensor Based Object Detection and Path Planning for Robot-Aided 3D Scanning. In: Ferraresi, C., Quaglia, G. (eds) Advances in Service and Industrial Robotics. RAAD 2017. Mechanisms and Machine Science, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-319-61276-8_37
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DOI: https://doi.org/10.1007/978-3-319-61276-8_37
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