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
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;
Conference_Titel :
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-7745-6
DOI :
10.1109/CDC.2010.5717586