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Robotic weed monitoring

机译:机器人杂草监测

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摘要

In this paper, an integrated management system for the planning and activation of a field monitoring task is presented. The architecture of the system is built around a mobile robotic unit. The internet-based architecture of the system includes a station unit that works as a mobile on-farm operating console, the mobile robotic unit and a field server for generating and storing maps. The hypothesis is that it is possible to automate the planning and execution of the operation of monitoring the in-field weed density and species distribution. The developed planning system includes the automatic field geometrical representation and the route planning for the mobile unit. For the field representation two algorithmic approaches for automated track generation were used. For the route planning, a graph-based field coverage algorithm and a discrete grid-based path planning method were used. The low computational requirements of the implemented algorithms make it feasible to adopt a real-time re-planning strategy in which a set of new planning problems are solved based on the latest information. The central part of such a planning, concerns the dynamic re-evaluation of the initial plan for sampling and routing based on the on-line analysis of the samples. This provides the basis for a fully sequential adaptive adjustment of the sampling procedure after each individual sampling. It is expected that such a dynamic targeted sampling and routing system will reduce the overall cost and time consumption of the weed monitoring operation.
机译:在本文中,提出了用于计划和激活现场监视任务的集成管理系统。该系统的体系结构围绕移动机器人单元构建。该系统基于Internet的体系结构包括充当移动农场操作控制台的工作站单元,移动机器人单元和用于生成和存储地图的现场服务器。假设是可以自动化计划和执行监测野外杂草密度和物种分布的操作。开发的计划系统包括自动场几何表示和移动单元的路线计划。对于场表示,使用了两种算法来自动生成轨道。对于路线规划,使用了基于图的字段覆盖算法和基于离散网格的路径规划方法。实施算法的低计算要求使得采用实时重新规划策略变得可行,在该策略中,基于最新信息可以解决一系列新的规划问题。此类计划的中心部分涉及基于样本的在线分析对样本和工艺路线的初始计划进行动态重新评估。这为每个单独采样后对采样过程进行完全顺序的自适应调整提供了基础。期望这种动态的有针对性的采样和路由系统将减少杂草监测操作的总成本和时间消耗。

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