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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Tijing Cai
Zhuopeng Yang
description 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.
doi_str_mv 10.1109/GCIS.2009.301
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subjects 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
title Path Plan in Gravity Aided Inertial Navigation Based on Ant Colony Algorithm
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