Comparison of parallel genetic algorithm and particle swarm optimization for real-time UAV path planning

IEEE Transactions on Industrial Informatics

Volumn 9, Issue 1, 2013, Pages 132-141

  Roberge, Vincent ^a   Tarbouchi, Mohammed ^a   Labonte, Gilles ^a  

^a ROYAL MILITARY COLLEGE OF CANADA   (Canada)

Author keywords

Genetic algorithm (GA); parallel computing; particle swarm optimization (PSO); path planning; unmanned aerial vehicles (UAVs)

Indexed keywords

3-D ENVIRONMENTS; AUTONOMOUS UNMANNED AERIAL VEHICLES; CIRCULAR ARC; COMMERCIAL OFF THE SHELVES; DYNAMIC PROPERTY; EXECUTION TIME; LINE SEGMENT; MILITARY ORGANIZATIONS; MULTI CORE; MULTI OBJECTIVE; OPTIMAL PATHS; PARALLEL GENETIC ALGORITHMS; PARALLEL IMPLEMENTATIONS; PARALLEL PROGRAMMING PARADIGMS; PARTICLE SWARM OPTIMIZATION ALGORITHM; QUASI-LINEAR; QUASI-OPTIMAL; REAL TIME PERFORMANCE; STATISTICAL SIGNIFICANCE;

FIXED WINGS; GENETIC ALGORITHMS; MULTICORE PROGRAMMING; PARALLEL ARCHITECTURES; PARALLEL PROCESSING SYSTEMS; PARALLEL PROGRAMMING; PARTICLE SWARM OPTIMIZATION (PSO); PROGRAM PROCESSORS; TRAFFIC SIGNALS; UNMANNED AERIAL VEHICLES (UAV);

MOTION PLANNING;

EID: 84871784432     PISSN: 15513203     EISSN: None     Source Type: Journal    
DOI: 10.1109/TII.2012.2198665     Document Type: Article

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