related work and intro first draft from toni

tex/egbib.bib

@@ -2613,4 +2613,81 @@ year = {2010}
   publisher={IEEE}
 }
 
+@article{GarciaPuyol2014,
+abstract = {Pedestrian navigation is an important ingredient for efficient multimodal transportation, such as guidance within large transportation infrastructures. A requirement is accurate positioning of people in indoor multistory environments. To achieve this, maps of the environment play a very important role. FootSLAM is an algorithm based on the simultaneous localization and mapping (SLAM) principle that relies on human odometry, i.e., measurements of a pedestrian's steps, to build probabilistic maps of human motion for such environments and can be applied using crowdsourcing. In this paper, we extend FootSLAM to multistory buildings following a Bayesian derivation. Our approach employs a particle filter and partitions the map space into a grid of adjacent hexagonal prisms with eight faces. We model the vertical component of the odometry errors using an autoregressive integrated moving average (ARIMA) model and extend the geographic tree-based data structure that efficiently stores the probabilistic map, allowing real-time processing. We present the multistory FootSLAM maps that were created from three data sets collected in different buildings (one large office building and two university buildings). Hereby, the user was only carrying a single foot-mounted inertial measurement unit (IMU). We believe the resulting maps to be strong evidence of the robustness of FootSLAM. This paper raises the future possibility of crowdsourced indoor mapping and accurate navigation using other forms of human odometry, e.g., obtained with the low-cost and nonintrusive sensors of a handheld smartphone.},
+author = {{Garcia Puyol}, Maria and Bobkov, Dmytro and Robertson, Patrick and Jost, Thomas},
+doi = {10.1109/TITS.2014.2303115},
+file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Garcia Puyol et al. - 2014 - Pedestrian simultaneous localization and mapping in multistory buildings using inertial sensors.pdf:pdf},
+issn = {15249050},
+journal = {IEEE Transactions on Intelligent Transportation Systems},
+keywords = {Indoor pedestrian navigation,inertial navigation,multistory localization and mapping,simultaneous localization and mapping (SLAM)},
+month = {aug},
+number = {4},
+pages = {1714--1727},
+shorttitle = {Intelligent Transportation Systems, IEEE Transacti},
+title = {{Pedestrian simultaneous localization and mapping in multistory buildings using inertial sensors}},
+volume = {15},
+year = {2014}
+}
+
+@article{Bandi2000,
+abstract = {This paper presents an efficient and robust technique for generating global motion paths for a human model in virtual environments. Initially, a scene is discretized using raster hardware to generate an environment map. An obstacle-free cell path sub-optimal according to Manhattan metric is generated between any two cells. Unlike 2D techniques present in literature, the proposed algorithm works for complex 3D environments suitable for video games and architectural walk-throughs. For obstacle avoidance, the algorithm considers both physical dimensions of the human and actions such as jumping, bending, etc. Path smoothening is carried out to keep the cell path as closely as possible to Euclidean straight-line paths.},
+author = {Bandi, Srikanth and Thalmann, Daniel},
+doi = {10.1016/S0925-7721(99)00046-2},
+file = {:home/toni/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Bandi, Thalmann - 2000 - Path finding for human motion in virtual environments.pdf:pdf},
+issn = {09257721},
+journal = {Computational Geometry},
+keywords = {Cellular paths,Heuristic search,Obstacle avoidance,Path planning,Pathfinding,Virtual walk-throughs},
+mendeley-tags = {Pathfinding},
+number = {1-3},
+pages = {103--127},
+title = {{Path finding for human motion in virtual environments}},
+volume = {15},
+year = {2000}
+}
+
+@inproceedings{tan2014agent,
+  title={Agent-based simulation of building evacuation using a grid graph-based model},
+  author={Tan, Lu and Lin, Hui and Hu, Mingyuan and Che, Weitao},
+  booktitle={IOP Conference Series: Earth and Environmental Science},
+  volume={18},
+  number={1},
+  pages={012123},
+  year={2014},
+  organization={IOP Publishing}
+}
+
+@inproceedings{Sun2011,
+abstract = {At present, application of GIS is in a process of transition from macro space to micro space, such as indoor space, a kind of micro environment that has a smaller scale than outdoor space. There have been some applications for indoor space, covering issues like path finding, emergency planning, object tracking, etc. Behind these applications, indoor spatial models are needed to illustrate how built environments are spatially represented. Although some modeling approaches have been proposed, most of them focus only on either structural or topological properties. In view of this problem, recently a grid graph-based modeling approach considering a built environment as a continuous framework is presented, which is able to combine both geometrical and structural properties. In this paper, we employ this approach to implement route analysis based on a hotel floor plan. The result might be applied to the planning for evacuation routes.},
+author = {Sun, Jing and Li, Xiang},
+booktitle = {Proceedings - 2011 19th International Conference on Geoinformatics, Geoinformatics 2011},
+doi = {10.1109/GeoInformatics.2011.5980680},
+isbn = {9781612848488},
+issn = {9781612848495},
+keywords = {evacuation planning,grid graph-based model,indoor space},
+month = {jun},
+pages = {1--4},
+publisher = {IEEE},
+shorttitle = {Geoinformatics, 2011 19th International Conference},
+title = {{Indoor evacuation routes planning with a grid graph-based model}},
+year = {2011}
+}
+
+@inproceedings{Brogan2003,
+abstract = {Pedestrian navigation is a complex function of human dynamics, a desired destination, and the presence of obstacles. People cannot stop and start instantaneously and their turning abilities are influenced by kinematic and dynamical constraints. A realistic model of human walking paths is an important development for entertainment applications and many classes of simulations. We present a novel behavioral model of path planning that extends previous models through its significant use of pedestrian performance statistics that were obtained during a suite of experiments. We develop an original interpretation of quantitative metrics for measuring a model’s accuracy, and use it to compare our path planning approach to a popular contemporary method. Results indicate that this new path planning model better fits natural human behavior than previous models.},
+author = {Brogan, D. C. and Johnson, N. L.},
+booktitle = {Proceedings - IEEE Workshop on Program Comprehension},
+doi = {10.1109/CASA.2003.1199309},
+file = {:home/toni/Documents/literatur/Realistic human walking paths.pdf:pdf},
+isbn = {0769519342},
+issn = {10928138},
+keywords = {Air safety,Animation,Humans,Kinematics,Legged locomotion,Navigation,Path planning,Robots,Testing,Turning},
+pages = {94--101},
+publisher = {IEEE Comput. Soc},
+shorttitle = {Computer Animation and Social Agents, 2003. 16th I},
+title = {{Realistic human walking paths}},
+volume = {2003-Janua},
+year = {2003}
+}
+