DocumentCode :
3516814
Title :
Joint self-localization and tracking of generic objects in 3D range data
Author :
Moosmann, Frank ; Stiller, Christoph
Author_Institution :
Inst. of Meas. & Control, Karlsruhe Inst. of Technol., Karlsruhe, Germany
fYear :
2013
fDate :
6-10 May 2013
Firstpage :
1146
Lastpage :
1152
Abstract :
Both, the estimation of the trajectory of a sensor and the detection and tracking of moving objects are essential tasks for autonomous robots. This work proposes a new algorithm that treats both problems jointly. The sole input is a sequence of dense 3D measurements as returned by multi-layer laser scanners or time-of-flight cameras. A major characteristic of the proposed approach is its applicability to any type of environment since specific object models are not used at any algorithm stage. More specifically, precise localization in non-flat environments is possible as well as the detection and tracking of e.g. trams or recumbent bicycles. Moreover, 3D shape estimation of moving objects is inherent to the proposed method. Thorough evaluation is conducted on a vehicular platform with a mounted Velodyne HDL-64E laser scanner.
Keywords :
SLAM (robots); image sensors; mobile robots; object detection; path planning; position control; robot vision; 3D range data; 3D shape estimation; dense 3D measurement sequence; generic object joint self-localization; generic objects tracking; mounted Velodyne HDL-64E laser scanner; multilayer laser scanners; object detection; recumbent bicycles; time-of-flight cameras; trajectory estimation; Estimation; Simultaneous localization and mapping; Target tracking; Three-dimensional displays; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation (ICRA), 2013 IEEE International Conference on
Conference_Location :
Karlsruhe
ISSN :
1050-4729
Print_ISBN :
978-1-4673-5641-1
Type :
conf
DOI :
10.1109/ICRA.2013.6630716
Filename :
6630716
Link To Document :
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