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Quantifying and improving laser range data when scanning industrial materials

MacLeod, Charles N. and Summan, Rahul and Dobie, Gordon and Pierce, S. Gareth (2016) Quantifying and improving laser range data when scanning industrial materials. IEEE Sensors Journal. ISSN 1530-437X

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This paper presents the procedure and results of a performance study of a miniature laser range scanner, along with a novel error correction calibration. Critically, the study investigates the accuracy and performance of the ranger sensor when scanning large industrial materials over a range of distances. Additionally, the study investigated the effects of small orientation angle changes of the scanner, in a similar manner to which it would experience when being deployed on a mobile robotic platform. A detailed process of error measurement and visualisation was undertaken on a number of parameters, not limited to traditional range data but also received intensity and amplifier gain. This work highlights that significant range distance errors are introduced when optically laser scanning common industrial materials, such as aluminum and stainless steel. The specular reflective nature of some materials results in large deviation in range data from the true value, with mean RMSE errors as high as 100.12 mm recorded. The correction algorithm was shown to reduce the RMSE error associated with range estimation on a planar aluminium surface from 6.48% to 1.39% of the true distance range.