DocumentCode :
438841
Title :
Navigation in complex unstructured environments
Author :
Wijesoma, W.S. ; Perera, L.D.L. ; Adams, M.D.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
Volume :
1
fYear :
2004
fDate :
6-9 Dec. 2004
Firstpage :
167
Abstract :
Autonomous navigation in complex unstructured environments has recently stimulated considerable interest among the robotics research community. This paper discusses the major challenges such as robust feature extraction and data association or the correspondence problem faced in achieving the above goal. The interrelationship between the feature extraction and the data association is elaborated by using the multi-frame multidimensional data association framework with concentration to simultaneous localization and map building problem in mobile robot navigation. It is explained how this data association framework can sustain under weak feature extraction scenarios in highly cluttered environments. Two suboptimal methods are presented to solve the resulting NP hard multidimensional assignment problems. Simulation results and experiments are presented to verity the claims above.
Keywords :
computational complexity; feature extraction; mobile robots; path planning; NP hard multidimensional assignment problems; autonomous navigation; complex unstructured environments; data association; feature extraction; mobile robot; multi-frame multidimensional data association framework; simultaneous localization and map building; Density measurement; Feature extraction; Navigation; Nearest neighbor searches; Robot localization; Robustness; Simultaneous localization and mapping; Target tracking; Vehicle dynamics; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th
Print_ISBN :
0-7803-8653-1
Type :
conf
DOI :
10.1109/ICARCV.2004.1468817
Filename :
1468817
Link To Document :
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