Vision-based lander safe zone detection and tracking for celestial body landing

Zhaotong Li; Jingmin Gao

doi:10.1117/12.2626552

20 December 2021 Vision-based lander safe zone detection and tracking for celestial body landing

Zhaotong Li, Jingmin Gao

Proceedings Volume 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021); 121550G (2021) https://doi.org/10.1117/12.2626552
Event: International Conference on Computer Vision, Application, and Design (CVAD 2021), 2021, Sanya, China

Abstract

This paper presents safe zone detection and tracking methods only based on vision for landing spacecraft on celestial bodies. Digital elevation model is used to generate a lunar surface image dataset. A modified residual-convolutional neural network is trained to extract craters from the trained binary images. For image sequences, safe landing areas without craters are recognized using Hough detection. Furthermore, when the camera loses the detected safe zone because of a violent shake, and then the safe zone moves back to the camera, our method can recognize it as beginning. The experimental proofs that our method improves the accuracy of crater identification and it can detect safe landing areas in the image sequence, In the case of large camera movement, the proposed method provides robust tracking results.

Citation Download Citation

Zhaotong Li and Jingmin Gao "Vision-based lander safe zone detection and tracking for celestial body landing", Proc. SPIE 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021), 121550G (20 December 2021); https://doi.org/10.1117/12.2626552

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KEYWORDS

Cameras

Transformers

Convolution

Image enhancement

Image segmentation

Binary data

Image processing

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