Lidar-based SLAM and autonomous navigation for forestry quadrotors

Quadrotor UAVs equipped with lidar have an indispensable role in forestry production. In this paper, an autonomous quadrotor with autonomous guidance and navigation ability is designed. Karto Slam algorithm for forestry quadrotor is utilized to accomplish the mission of situation awareness, in which...

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Bibliographic Details
Published in2018 IEEE CSAA Guidance, Navigation and Control Conference (CGNCC) pp. 1 - 6
Main Authors Hu, Xuejun, Wang, Meishan, Qian, Chenghao, Huang, Chengjie, Xia, Yu, Song, Ming
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2018
Subjects
Agriculture
airborne LIDAR
algorithm
Forestry
Heuristic algorithms
Karto Slam
Laser radar
Optimization
Path planning
RRT
Simultaneous localization and mapping
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Summary:Quadrotor UAVs equipped with lidar have an indispensable role in forestry production. In this paper, an autonomous quadrotor with autonomous guidance and navigation ability is designed. Karto Slam algorithm for forestry quadrotor is utilized to accomplish the mission of situation awareness, in which the SPA method and the LM algorithm are used to make the map constructed in practical application with good accuracy and closed-loop characteristics. The RRT* algorithm is used to acquire the sub-optimal path further. The results show that the system can accomplish the task well in the presence of a large number of tree obstacles and has lower computational complexity.
DOI:10.1109/GNCC42960.2018.9018923