前沿:自动除草系统的检测、驱动和规划中的自主性

IF 1.4 4区农林科学 Q3 AGRICULTURAL ENGINEERING

Transactions of the ASABE Pub Date : 2021-01-01 DOI:10.13031/TRANS.14085

P. Pandey, H. Dakshinamurthy, Sierra N. Young

引用次数: 9

摘要

最近的研究和开发工作集中在开发更小的便携式机器人除草系统上。深度学习方法实现了准确、快速、鲁棒的杂草检测和识别。正在开发的其他关键技术包括精密驱动和多车规划。关键词:人工智能，自动化系统，自动除草，杂草控制

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Frontier: Autonomy in Detection, Actuation, and Planning for Robotic Weeding Systems

HighlightsRecent research and development efforts center around developing smaller, portable robotic weeding systems.Deep learning methods have resulted in accurate, fast, and robust weed detection and identification.Additional key technologies under development include precision actuation and multi-vehicle planning. Keywords: Artificial intelligence, Automated systems, Automated weeding, Weed control.

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来源期刊

Transactions of the ASABE AGRICULTURAL ENGINEERING-

CiteScore

2.30

自引率

0.00%

发文量

审稿时长

6 months

期刊介绍： This peer-reviewed journal publishes research that advances the engineering of agricultural, food, and biological systems. Submissions must include original data, analysis or design, or synthesis of existing information; research information for the improvement of education, design, construction, or manufacturing practice; or significant and convincing evidence that confirms and strengthens the findings of others or that revises ideas or challenges accepted theory.