Autonomous mowing in agriculture: Current status, needs, and future opportunities

摘要

• Comprehensive review of autonomous mowing in agricultural contexts. • Review needs, gaps, and current research agricultural autonomous mowing. • Integrated review of mower types, sensing, navigation, and relevant AI & IoT technologies. • Comparative survey of commercial robotic mowers and capability gaps. • Explores concept of robotic mowers as multi-tasking agricultural robotic platforms. Autonomous mowing between rows in orchards, vineyards, berry farms, and other specialty crop systems can reduce labor costs, improve safety on uneven terrain, and increase farm productivity and profitability. Mowing is also central to haymaking, where timely cutting affects forage quality and livestock nutrition. Despite its importance, autonomous agricultural mowing remains understudied, and lagging compared to other agricultural operations such as weeding and harvesting. Additionally, limited research prototypes and commercial or near-commercial systems demonstrate reliable autonomous performance in agricultural environments. Most existing reviews on mowing focus on commercial or residential mowing, while only a few specifically address challenges or opportunities unique to mowing in agricultural contexts. This review provides a structured and comprehensive analysis of autonomous mowing technologies in agriculture. First, it examines overall trends in agricultural robotics research and, through a comparative analysis of farming operations, demonstrates that automation in agricultural mowing remains relatively underexplored. It then reviews current trends in automation specific to agricultural mowing, highlighting existing approaches and their limitations. Next, the review identifies key gaps and unmet needs, emphasizing challenges related to unstructured terrain, crop variability, sensing reliability, and operational robustness. The review further surveys of recent advances in intelligent hardware, software frameworks, and artificial intelligence relevant to mowing systems, including mower designs, cutting mechanisms, navigation strategies, and path-planning methods. This analysis focuses on general mowing technologies rather than agricultural-specific implementations, revealing a mismatch between technological progress and field-ready requirements. An industry-oriented overview of automated mower platforms is also presented, noting that most commercially available systems are designed for urban or highly managed environments and remain poorly adapted to agricultural use. Finally, the review highlights emerging opportunities enabled by autonomous, multi-functional agricultural mowers, particularly platforms capable of integrating mowing with tasks such as weed detection, spraying, soil sampling, and plant-health monitoring. By synthesizing fragmented research and clarifying development pathways, this work establishes a comprehensive reference for advancing autonomous mowing systems in real agricultural settings.