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176                                    Autonomous Mobile Robots




                                     Laser range data
                                                                                 Circle center
                                                                                 coordinates

                                     Next scan point


                                                          Increment all cells
                                    Determine weighting   at distance R from   Find accumulator
                                      by multiplying      corresponding cell      cell with
                                      by point range      in accumulator grid    most votes
                                                            by weighting


                                FIGURE 4.14 Flowchart of the circular Hough transform detection process.

                                circles. One important property of circles is that they are highly symmetric and
                                so appear identical when viewed from any angle; this greatly eases the burden
                                of detection. Also, the range data has an inherent sequence that is not obvious in
                                Cartesian coordinates. Detection of a circle occurs when a sequence of adjacent
                                points lie close to the circumference of that circle. Relaxing the requirement
                                for the detection of occluded targets allows the following algorithm shown in
                                Figure 4.15b.
                                   The algorithm assumes the center of the circular target is at the scan angle of
                                the current scan point being analyzed. The mean of the least squares differences
                                is then calculated by Equation (4.38) and Equation (4.39). Scan angles with this
                                quantity below a threshold (comparable to the accuracy of the laser scanner)
                                are likely contenders for having the center of the target circle situated along
                                them. Figure 4.15a illustrates the geometry involved with laser scan points
                                depicted by crosses. Point A is the current scan point being evaluated and the
                                circle represents the search target. The candidate circle for A is assumed to be
                                positioned with center C, as shown on the line OA where O is the origin of the
                                laser scan. Assuming the laser scan returns points evenly distributed over θ then
                                the number of nearest neighbors to be incorporated is determined. Points that
                                                    ˆ
                                lie within an angle of AOB from A are candidate points where
                                                                     R
                                                     AOB = arcsin                         (4.35)
                                                       ˆ
                                                                  (R + OA)

                                and R is the radius of the circular landmark.
                                   Care has to be taken regarding scan points lying near D and B, which are
                                subject to glancing edge effects. The causes of these effects are specular reflec-
                                tion and pixel mixing which occurs when the laser spot spans an environmental




                                 © 2006 by Taylor & Francis Group, LLC



                                FRANKL: “dk6033_c004” — 2006/3/31 — 16:42 — page 176 — #28
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