Desertification Land Sea-buckthorn Planting Robot Based on YOLOv5 Algorithm

DOI: https://doi.org/10.62517/jlsa.202407206

Author(s)

Yi Zhang, Mengmeng Ma, Tao Gong, Yahui Pei*

Affiliation(s)

College of Electrical Engineering, Southwest Minzu University, Chengdu, China *Corresponding Author.

Abstract

Desertification poses a serious threat to both humanity and ecosystems, and planting sea-buckthorn can help prevent wind erosion, maintain soil and water, and play a crucial role in improving ecological conditions. Traditional methods of planting sea-buckthorn are characterized by high labor costs and lengthy time cycles, making them inadequate for the demands of large-scale afforestation. To address this issue, this paper presents a tree-planting robot capable of planting sea-buckthorn on desertification land. The robot is equipped with a self-developed integrated mechanical arm for grasping and planting, utilizing SLAM mapping and RTT path planning for autonomous navigation and optimal route planning. Additionally, it features a vision recognition system based on deep learning this tree-planting robot effectively reduces labor, saves time and economic costs, and contributes to the improvement of land desertification.

Keywords

Sea-buckthorn Planting Robot; Integrated Mechanical Arm for Grasping and Planting; SLAM Mapping; Vision Recognition

References

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