Single-camera-based sand volume estimation of an excavator bucket
For intelligent support of consruction site, it is needed to estimate the workload of excavator bucket. But, previous studies are not practical by the reason of non-real-time processing or implementation cost. In this paper, a novel method, which use only a single camera and image processing technique to estimate the workload of excavator bucket, is addressed based on the assumption of actual bucket size, uniformity of sand, and geometric model for the shape of excavator bucket and the shape of accumulated sand in the bucket. For the ease of analysis, the state of bucket was divided into three states, Under-Struck state, Struck state, and Heaped state, depending on the amount of sand accumulation. Specially, Heaped state was also divided into Sharply-Heaped state and Smoothly-Heaped state depending on the relative height of peak point of the sand pyramid in the view of photographed image. By finding the positions of bucket corner points, highest vertex of the sand pyramid and uppermost edge point of the sand region in photographed image, various geometric parameters are found by using mathematical modeling. Hereafter, the volume of sand in the bucket is estimated by using the ratio between the length of the actual bucket and the length of the bucket in the photographed image. Finally, the workload of the excavator bucket represented by the mass is obtained by multiplying the pre-defined density of sand. Experimental results show that the accuracy of the proposed method is 93.7% on average.
KeywordsSand volume estimation Single camera Image processing Excavator bucket
This research was partially supported by the MIST (Ministry of Science and ICT), Korea, Under the national program for excellence in SW supervised by the IITP (Institute for Information & Communications Technology Promotion) (2016-0-00017), and partially supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2015R1D1A1A09061368), and partially supported by the Starting growth Technological R&D program of SMBA [S2436536], and partially supported by the KIAT (Korea Institute for Advancement of Technology) grant funded by the Korea Government (MOTIE: Ministry of Trade Industry and Energy) (No. N0001884, HRD program for Embedded Software). And the authors would like to give special thanks to Mr. Hyun-Mo Yang for his assistance to the implementation of image processing algorithm for this research.
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