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Development of Smart Viticulture System Using Autonomous Robots

使用自主机器人开发智能葡萄栽培系统

基本信息

批准号：
21K14117
负责人：
ラワンカルアビジート
金额：
$ 2.08万
依托单位：
Kitami Institute of Technology
依托单位国家：
日本
项目类别：
Grant-in-Aid for Early-Career Scientists
财政年份：
2021
资助国家：
日本
起止时间：
2021-04-01 至 2024-03-31
项目状态：
已结题

项目摘要

This research aims at developing a smart viticulture system through the use of autonomous robots and AI. Smart viticulture aims at reducing the burden of farmers by automating tasks like vineyard monitoring, inspection, yield estimation, and harvesting of grapes.In FY2022, the accuracy of the monitoring system developed in previous FY was improved through the use of Deep Learning based landmark detection. The previously developed system relied on landmark (pillar) detection based on color, which caused inaccuracies during the change of illumination conditions and rain. A convolutional neural network based model was trained and evaluated to be robust against dynamic changes in the environment and gave better estimation of the landmarks. This improved the overall SLAM (Simultaneous Localization and Mapping) module which was developed without the use of GPS, and relies on local-only features for cost-cutting. In Addition, a deep learning CNN model was developed for detecting grapes/branches and their conditions (ripe, almost-ripe, raw). A weed detection model has been developed. The harvesting module is developed in simulator and a real-world manufacturing and test is planned for FY2023. Algorithms for robot navigation in structured vineyard environment, obstacle avoidance, alarm system, multi-robot cooperation algorithms for vineyard, have also been developed and results have been published in conferences.

该研究旨在通过使用自主机器人和人工智能开发智能葡萄栽培系统。智能葡萄栽培旨在通过自动化葡萄园监控、检查、产量估算和葡萄收获等任务来减轻农民的负担。在2022财年，通过使用基于深度学习的地标检测，上一财年开发的监控系统的准确性得到了提高。以前开发的系统依赖于基于颜色的地标（柱子）检测，这在照明条件和降雨的变化期间导致不准确。基于卷积神经网络的模型经过训练和评估，对环境中的动态变化具有鲁棒性，并对地标进行了更好的估计。这改进了整个SLAM（同步定位和地图）模块，该模块在开发时没有使用GPS，并且依赖于仅本地功能来削减成本。此外，还开发了一个深度学习CNN模型，用于检测葡萄/树枝及其状况（成熟，即将成熟，生）。杂草检测模型已经开发。采集模块在模拟器中开发，并计划于2023财年进行实际生产和测试。结构化葡萄园环境中的机器人导航算法，避障，报警系统，葡萄园的多机器人合作算法，也已经开发出来，结果已在会议上发表。