Obstacles detection method for UAV based on monocular vision and laser projection

LIU Feng; WANG Zan; WANG Xiangjun

doi:10.5768/JAO202344.0107002

Volume 44 Issue 1

Jan. 2023

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LIU Feng, WANG Zan, WANG Xiangjun. Obstacles detection method for UAV based on monocular vision and laser projection[J]. Journal of Applied Optics, 2023, 44(1): 202-210. doi: 10.5768/JAO202344.0107002

Citation:

LIU Feng, WANG Zan, WANG Xiangjun. Obstacles detection method for UAV based on monocular vision and laser projection[J]. Journal of Applied Optics, 2023, 44(1): 202-210. doi: 10.5768/JAO202344.0107002

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Obstacles detection method for UAV based on monocular vision and laser projection

doi: 10.5768/JAO202344.0107002

LIU Feng^{1, 2
,},
WANG Zan^{1, 2
,
,},
WANG Xiangjun^{1, 2}

1.
State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China
2.
Key Laboratory of Micro Optical Electro Mechanical System Technology (Ministry of Education), Tianjin University, Tianjin 300072, China

Received Date: 2022-05-10
Rev Recd Date: 2022-06-13

Available Online: 2022-11-23

Publish Date: 2023-01-17

Abstract

Abstract

In order to meet the requirement of active obstacle avoidance of microminiature unmanned aerial vehicle (UAV) in flight mission, an obstacles detection method based on monocular vision and active laser lattice projection of microminiature UAV for obstacles avoidance was proposed. The projected laser lattice patterns were collected by a monocular camera, and through the processes of image segmentation, clustering and centroid extraction, the ambiguity of the characteristic consistent laser point was quickly eliminated by the constraint of the laser line equation of the image plane. The laser points were used to detect the distribution of obstacles in the front space of the UAV. The experimental results show that the relative error of obstacles detection is within 1.5% when the baseline distance is 65 mm and the working distance is 7 m. The proposed method has high accuracy and low time complexity, and can meet the requirements for obstacles detection methods of microminiature UAV with low computing power, which provides the data support for the generation of further obstacles avoidance strategies.
- obstacles detection,
- microminiature unmanned aerial vehicle,
- monocular vision,
- dimensional orientation

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References(15)

References

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