In this paper we report the application of a laser speckle odometer to a mobile industrial robot in a typical factory floor environment. The suitability of typical floor surfaces and features is assessed in terms of the ability to form speckle patterns with sufficient signal to noise for correlation-based processing. All tested surfaces including concrete, rubber tile, dried paint and oil stains, and hazard tapes were found to be suitable. A comparison of the velocimetry sensor output to the industrial robot’s internal SLAM and wheel encoder data is presented with good agreement of < 0.3mm/s at tested speeds of up to 250mm/s. Finally, a comparison of speckle odometry to the robot’s internal SLAM based navigation will be presented using a laser tracker to provide ground-truth measurement data. Both techniques were found to perform similarly, with errors of up to 80mm when traversing a 16m square path of 4m sides. The laser speckle odometry was however found to perform significantly better over the initial sides of the path with a maximum error of < 10mm in comparison to < 47mm for the robot’s internal odometry.
A non-contact optical technique employing dual-wavelength laser speckle is investigated for absolute angle measurement. The approach uses the separation of the speckle patterns formed by two closely spaced illumination wavelengths to determine the angle of a surface. Autocorrelation is performed on a single exposure containing both speckle patterns to find their relative displacement, which is directly related to the absolute surface angle. This absolute angle determination offers an advantage over previous techniques using laser speckle that require a reference image. The underlying theory linking the speckle pattern displacement and the surface angle is presented, along with a proof-of-concept sensor. Experimental results from the sensor confirm the validity of the theory, with measurements demonstrating a mean difference from applied angles of 0.136°.
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