feierband. good progress in related work.

tex/egbib.bib

@@ -2567,3 +2567,50 @@ title = {{Analysis of a complex of statistical variables into Principal Componen
 year = {1933}
 }
 
+@article{Thrun2003,
+abstract = {This article describes a new algorithm for acquiring occupancy grid maps with mobile robots. Existing occupancy grid mapping algorithms decompose the high-dimensional mapping problem into a collection of one-dimensional problems, where the occupancy of each grid cell is estimated independently. This induces conflicts that may lead to inconsistent maps, even for noise-free sensors. This article shows how to solve the mapping problem in the original, high-dimensional space, thereby maintaining all dependencies between neighboring cells. As a result, maps generated by our approach are often more accurate than those generated using traditional techniques. Our approach relies on a statistical formulation of the mapping problem using forward models. It employs the expectation maximization algorithm for searching maps that maximize the likelihood of the sensor measurements.},
+author = {Thrun, Sebastian},
+doi = {10.1023/A:1025584807625},
+file = {:home/toni/Documents/literatur/fusion16/thrun.iros01-occmap.pdf:pdf},
+isbn = {0-7803-6612-3},
+issn = {09295593},
+journal = {Autonomous Robots},
+keywords = {Bayesian techniques,Mapping,Mobile robotics,Probabilistic inference,Robot navigation,SLAM},
+language = {en},
+number = {2},
+pages = {111--127},
+pmid = {563334},
+publisher = {Kluwer Academic Publishers},
+title = {{Learning occupancy grid maps with forward sensor models}},
+volume = {15},
+year = {2003}
+}
+
+@article{Li2010,
+abstract = {While recent years have witnessed noticeable development of indoor GIS, there is still a lack of clear consensus on the modeling principles that should support such applications. The objective of the research presented in this paper is to represent two-dimensional (2D) indoor spaces with a grid graph-based model that takes into account the structural and spatial properties of an indoor space. The model developed considers a built environment as a frame of reference at different levels of granularity using a grid graph-based representation. The advantage of the modeling approach is that it combines structural and topological properties as well as implicitly taking into account the metric of space, this being often overlooked by most existing indoor space models. Several types of indoor space analysis are employed to illustrate the potential of the proposed model, such as route and diffusion analysis, centrality and topological analysis.},
+author = {Li, Xiang and Claramunt, Christophe and Ray, Cyril},
+doi = {10.1016/j.compenvurbsys.2010.07.006},
+file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Li, Claramunt, Ray - 2010 - A grid graph-based model for the analysis of 2D indoor spaces.pdf:pdf},
+issn = {01989715},
+journal = {Computers, Environment and Urban Systems},
+keywords = {Grid graph-based representation,Indoor spaces,Network,Structural-based modeling},
+month = {nov},
+number = {6},
+pages = {532--540},
+title = {{A grid graph-based model for the analysis of 2D indoor spaces}},
+volume = {34},
+year = {2010}
+}
+
+@article{elfes1989using,
+  title={Using occupancy grids for mobile robot perception and navigation},
+  author={Elfes, Alberto},
+  journal={Computer},
+  volume={22},
+  number={6},
+  pages={46--57},
+  year={1989},
+  publisher={IEEE}
+}
+
+