3D data acquisition gets increasingly important for mobile robotics in general and for Safety, Security and Rescue Robotics (SSRR) in particular. 3D data allows for example to estimate the size of gaps, to construct realistic maps of unstructured disaster environments, or to detect human victims from shape. The SwissRanger SR-3000 time-of-flight 3D camera is a popular device for acquiring 3D range data as it offers the fast update rates of a camera with a resolution of 176 × 144 pixel at a reasonable cost. But the SR-3000 suffers - like any device using phase differences of modulated light - from the fundamental problem of wrap around error, i.e., distances that are a multiple of the wavelength of the modulated ranging signal can not be distinguished. The standard solution to this problem is to use an amplitude threshold, i.e., to discard pixels which are relatively dark and hence assumed to be far away. Here, a significant improvement to the standard method is presented that relates measured brightness and distance and also takes the geometry of the modulated light source into account. It is shown that a significantly higher amount of valid range data can be acquired with this new method.
['Jann Poppinga', 'Andreas Birk']
A Novel Approach to Efficient Error Correction for the SwissRanger Time-of-Flight 3D Camera