UAV Path Re-planning of Multi-step Optimization Based on LRTA* Algorithm

  • Li Fu
  • Kun Zhu
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 173)


For the UAV with the flight environment of unknown threats in advance, the paper combine self-learning A* real-time algorithm with node expansion method based on Five-fork Tree, then application of multi-step optimizing search algorithm re-plan path. When the UAV’s detectors detect unknown threats in flight environment, the algorithm modify the affected tracks according to new environmental information in order to get a new track. Finally through a numerical simulation demonstrates the effectiveness of the algorithm.


Path Planning Target Node Route Planning Unmanned Aircraft Reference Trace 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.School of AutomationShenyang Aerospace UniversityShenyangChina

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