Abstract
We will demonstrate the sensor and data fusion concept of the 2007 DARPA Urban Challenge vehicle assembled by Team CarOLO, Technische Universität Braunschweig. The perception system is based on a hybrid fusion concept, combining object and grid based approaches in order to comply with the requirements of an urban environment. A variety of sensor systems and technologies is applied, providing a 360 degree view area around the vehicle. Within the object based subsystem, obstacles (static and dynamic) are tracked using an Extended Kalman Filter capable of tracking arbitrary contour shapes. Additionally, the grid based subsystem extracts drivability information about the vehicle’s driveway by combining the readings of laser scanners, a mono and a stereo camera system using a Dempster-Shafer based data fusion approach. ...
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References
Frank, A.: On Kuhn’s Hungarian Method - A tribute from Hungary. Egrervary Research Group, Pazmany P. setany 1/C, H1117, Budapest, Hungary
Becker, J.-C.: Fusion der Daten der objekterkennenden Sensoren eines autonomen Straenfahrzeugs (german). Ph.D. thesis, Institute of Control Engineering, Braunschweig, Germany (March 2002)
Pitteway, M.L.V.: Algorithmn for Drawing Ellipses or Hyperbolae with a Digital Plotter. Computer Journal 10(3), 282–289 (1967)
Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press, Princeton (1976)
Shafer, G.: Perspectives on the theory and practice of belief functions. International Journal of Approximate Reasoning 3, 1–40 (1990)
Thrun, S., et al.: Stanley: The Robot That Won The DARPA Grand Challenge. Technical report, Stanford University, Stanford (2005)
Heikkilá, J., Silvén, O.: Calibration procedure for short focal length off-the-shelf CCD cameras. In: Proc. 13th International Conference on Pattern Recognition, Vienna, Austria, pp. 166–170 (1996)
The Open CV Library, Internet, http://opencvlibrary.sourceforge.net
Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics, Massachusetts Institute of Technology. The MIT Press, Cambridge, Massachusetts (2005)
Rosenblatt, J.: Damn: A distributed architecture for mobile navigation. Ph.D. dissertation, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA (1997)
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Effertz, J. (2008). Sensor Architecture and Data Fusion for Robotic Perception in Urban Environments at the 2007 DARPA Urban Challenge. In: Sommer, G., Klette, R. (eds) Robot Vision. RobVis 2008. Lecture Notes in Computer Science, vol 4931. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78157-8_21
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DOI: https://doi.org/10.1007/978-3-540-78157-8_21
Publisher Name: Springer, Berlin, Heidelberg
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