Path Plan in Gravity Aided Inertial Navigation Based on Ant Colony Algorithm

According to the characteristics of gravity aided inertial navigation, the paper presents an ant colony algorithm (ACA) which takes gravity correlation coefficients as heuristic factors, and the simulation of the algorithm based on simulated gravity anomaly map is carried out. The results show paths...

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Bibliographische Detailangaben
Hauptverfasser:	Zeyuan Lu, Tijing Cai, Zhuopeng Yang
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Ant Colony Algorithm Ant colony optimization Genetic algorithms Gravity Gravity Aided Inertial Navigation Inertial navigation Instruments Intelligent systems Numerical simulation Path Plan Robots Stochastic processes Unmanned aerial vehicles
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Beschreibung
Zusammenfassung:	According to the characteristics of gravity aided inertial navigation, the paper presents an ant colony algorithm (ACA) which takes gravity correlation coefficients as heuristic factors, and the simulation of the algorithm based on simulated gravity anomaly map is carried out. The results show paths derived from the algorithm are short, and nodes of paths have lower gravity correlation coefficient. The validity of ACA in path plan for gravity navigation is verified by simulation.
ISSN:	2155-6083 2155-6091
DOI:	10.1109/GCIS.2009.301