A Localizability Constraint-Based Path Planning Method for Unmanned Aerial Vehicle

  • Behnam Irani
  • Weidong Chen
  • Jingchuan Wang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 867)


As unmanned aerial vehicles (UAVs) are used in challenging environments to carry out various complex tasks, a satisfactory level of localization performance is required to ensure safe and reliable operations. 3D laser range finder (LRF)-based localization is a suitable approach in areas where GPS signal is not accesible or unreliable. During navigation, environmental information and map noises at different locations may contribute differently to a UAV’s localization process, causing it to have dissimilar ability to localize itself using LRF readings, which is referred to as localizability in this paper. We propose a localizability constraint (LC) based path planning method for UAV, which plans the navigation path according to LRF sensor model to achieve higher localization performance throughout the path. Paths planned with and without LC are compared and discussed through simulations in outdoor urban and wilderness environemnts. We show that the proposed method effectively reduces the localization error along the planned paths.


Unmanned aerial vehicle Path planning Localizability Localization Navigation 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Key Laboratory of System Control and Information Processing, Department of Automation, Ministry of Education of ChinaShanghai Jiao Tong UniversityShanghaiChina

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