Review of Simultaneous Localization and Mapping Technology in the Agricultural Environment

被引:0
|
作者
Wei Y. [1 ,2 ,3 ,4 ]
Zhou B. [1 ,2 ]
Zhang J. [1 ,2 ]
Sun L. [1 ,2 ]
An D. [1 ,2 ,3 ,4 ]
Liu J. [1 ,2 ,3 ]
机构
[1] National Innovation Center for Digital Fishery, China Agricultural University, Beijing
[2] College of Information and Electrical Engineering, China Agricultural University, Beijing
[3] Key Laboratory of Smart Farming Technologies for Aquatic Animals and Livestock, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing
[4] Beijing Engineering and Technology Research Centre for Internet of Things in Agriculture, Beijing
关键词
agricultural environment; agricultural robots; environment map construction; localization; navigation; simultaneous localization and mapping (SLAM);
D O I
10.15918/j.jbit1004-0579.2023.015
中图分类号
学科分类号
摘要
Simultaneous localization and mapping (SLAM) is one of the most attractive research hotspots in the field of robotics, and it is also a prerequisite for the autonomous navigation of robots. It can significantly improve the autonomous navigation ability of mobile robots and their adaptability to different application environments and contribute to the realization of real-time obstacle avoidance and dynamic path planning. Moreover, the application of SLAM technology has expanded from industrial production, intelligent transportation, special operations and other fields to agricultural environments, such as autonomous navigation, independent weeding, three-dimensional (3D) mapping, and independent harvesting. This paper mainly introduces the principle, system framework, latest development and application of SLAM technology, especially in agricultural environments. Firstly, the system framework and theory of the SLAM algorithm are introduced, and the SLAM algorithm is described in detail according to different sensor types. Then, the development and application of SLAM in the agricultural environment are summarized from two aspects: environment map construction, and localization and navigation of agricultural robots. Finally, the challenges and future research directions of SLAM in the agricultural environment are discussed. © 2023 Beijing Institute of Technology. All rights reserved.
引用
收藏
页码:257 / 274
页数:17
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