DocumentCode :
2574993
Title :
Beamlet-like data processing for accelerated path-planning using multiscale information of the environment
Author :
Lu, Yibiao ; Huo, Xiaoming ; Tsiotras, Panagiotis
Author_Institution :
H. Milton Stewart Sch. of Ind. & Syst. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fYear :
2010
fDate :
15-17 Dec. 2010
Firstpage :
3808
Lastpage :
3813
Abstract :
We consider the deterministic path-planning problem dealing with the single-pair shortest path on a given graph. We propose a multiscale version of the well known A* algorithm (m-A*), which utilizes information of the environment at distinct scales. This information is collected via a bottom-up fusion method. Comparing with existing algorithms such as Dijkstra´s or A*, the use of multiscale information leads to an improvement in terms of computational complexity.
Keywords :
computational complexity; graph theory; path planning; sensor fusion; bottom-up fusion method; computational complexity; data processing; multiscale information; path planning; shortest path search algorithm; Artificial neural networks; Complexity theory; Heuristic algorithms; Joining processes; Nearest neighbor searches; Path planning; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location :
Atlanta, GA
ISSN :
0743-1546
Print_ISBN :
978-1-4244-7745-6
Type :
conf
DOI :
10.1109/CDC.2010.5717586
Filename :
5717586
Link To Document :
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