By Andreas Nüchter
The monograph written by way of Andreas Nüchter is targeted on buying spatial types of actual environments via cellular robots. The robot mapping challenge is usually often called SLAM (simultaneous localization and mapping). 3D maps are essential to stay away from collisions with advanced hindrances and to self-localize in six levels of freedom
(x-, y-, z-position, roll, yaw and pitch angle). New ideas to the 6D SLAM challenge for 3D laser scans are proposed and a large choice of purposes are presented.
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Additional info for 3D Robotic Mapping: The Simultaneous Localization and Mapping Problem with Six Degrees of Freedom
1) and maximizes the number of corresponding points. 1 Direct Solutions of the ICP Error Function In every iteration the optimal transformation (R, t) for minimizing the error function E(R, t) in Eq. 1) has to be computed. There exist diﬀerent strategies to ﬁnd the minimum that can be divided into direct and indirect methods. 1 The ICP Algorithm 37 The simulation of a physical spring system belongs to the indirect methods [27, 116]. Here the distances between the closest points that are summed in Eq.
Therefore, stereo algorithms do no not match pixel, but compare image regions instead (cf. 19). 7) [i,j]∈R f (i, j)g(i, j). 8) [i,j]∈R Here the images are f and g. 7) is called sum of squared distances (SSD) and has to be minimized. If image regions are identical the numerical value is 0. 8) is the cross correlation (CC) and shows a maximum for identical image regions. Fig. 19: Left: Results using a small search window. Right: large search window. 20 shows two disparity maps. Comparing image regions yields an approximation, since image regions might be visible only in one camera and might not have correspondences.
51]. Fig. 2 Left: Pioneer DX-2 robot equipped with two SICK laser scanner (PLS 100) for 3D mapping. The upward pointing scanner is used to acquire 3D data. Middle and right: Acquired 3D maps. Figure courtesy of S. Thrun. 1 Categorization of Robotic Mapping Algorithms 31 Fig. 3 Slice-wise 6D SLAM on the robot Stanley. Stanley won the DARPA Grand Chellange 2005. Figure courtesy of S. Thrun. estimation problem. Besides the robot pose, positions of landmarks are estimated. , a second encounter of a previously visited area of the environment, play a special role here.
3D Robotic Mapping: The Simultaneous Localization and Mapping Problem with Six Degrees of Freedom by Andreas Nüchter