文章基本信息

标题：Localization and Mapping for Robots in Agriculture and Forestry: A Survey
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作者：André Silva Aguiar ; Filipe Neves dos Santos ; José Boaventura Cunha 等
期刊名称：Robotics
电子版ISSN：2218-6581
出版年度：2020
卷号：9
期号：4
页码：97-119
DOI：10.3390/robotics9040097
出版社：MDPI Publishing
摘要：Research and development of autonomous mobile robotic solutions that can perform several active agricultural tasks (pruning, harvesting, mowing) have been growing. Robots are now used for a variety of tasks such as planting, harvesting, environmental monitoring, supply of water and nutrients, and others. To do so, robots need to be able to perform online localization and, if desired, mapping. The most used approach for localization in agricultural applications is based in standalone Global Navigation Satellite System-based systems. However, in many agricultural and forest environments, satellite signals are unavailable or inaccurate, which leads to the need of advanced solutions independent from these signals. Approaches like simultaneous localization and mapping and visual odometry are the most promising solutions to increase localization reliability and availability. This work leads to the main conclusion that, few methods can achieve simultaneously the desired goals of scalability, availability, and accuracy, due to the challenges imposed by these harsh environments. In the near future, novel contributions to this field are expected that will help one to achieve the desired goals, with the development of more advanced techniques, based on 3D localization, and semantic and topological mapping. In this context, this work proposes an analysis of the current state-of-the-art of localization and mapping approaches in agriculture and forest environments. Additionally, an overview about the available datasets to develop and test these approaches is performed. Finally, a critical analysis of this research field is done, with the characterization of the literature using a variety of metrics.
关键词：localization and mapping; autonomous navigation; agriculture; forestry localization and mapping ; autonomous navigation ; agriculture ; forestry