Paper
22 October 1993 Practical approach to apply range image sensors in machine automation
Ilkka Moring, Jussi Paakkari
Author Affiliations +
Proceedings Volume 2066, Industrial Optical Sensing and Metrology: Applications and Integration; (1993) https://doi.org/10.1117/12.162097
Event: Optical Tools for Manufacturing and Advanced Automation, 1993, Boston, MA, United States
Abstract
In this paper we propose a practical approach to apply range imaging technology in machine automation. The applications we are especially interested in are industrial heavy-duty machines like paper roll manipulators in harbor terminals, harvesters in forests and drilling machines in mines. Characteristic of these applications is that the sensing system has to be fast, mid-ranging, compact, robust, and relatively cheap. On the other hand the sensing system is not required to be generic with respect to the complexity of scenes and objects or number of object classes. The key in our approach is that just a limited range data set or as we call it, a sparse range image is acquired and analyzed. This makes both the range image sensor and the range image analysis process more feasible and attractive. We believe that this is the way in which range imaging technology will enter the large industrial machine automation market. In the paper we analyze as a case example one of the applications mentioned and, based on that, we try to roughly specify the requirements for a range imaging based sensing system. The possibilities to implement the specified system are analyzed based on our own work on range image acquisition and interpretation.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ilkka Moring and Jussi Paakkari "Practical approach to apply range image sensors in machine automation", Proc. SPIE 2066, Industrial Optical Sensing and Metrology: Applications and Integration, (22 October 1993); https://doi.org/10.1117/12.162097
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KEYWORDS
Sensors

Data modeling

Image segmentation

Image sensors

Sensing systems

Detection and tracking algorithms

LIDAR

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