农业机器人综合路线规划系统

G. Asiminari, Vasileios Moysiadis, D. Kateris, Patrizia Busato, Caicong Wu, C. Achillas, Claus Sørensen, Simon Pearson, D. Bochtis
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引用次数: 0

摘要

在从精准农业(针对特定任务的方法)向智能农业(针对特定系统的方法)过渡的过程中,有必要建立和评估机器人系统,使其成为持续双向连接和互动的整体集成系统的一部分。本文介绍了创建农业机器人集成系统的第一步,即在智能农业实施的总体范围内,实现无人地面车辆(UGV)与农场管理信息系统(FMIS)之间的双向通信。在这一初始步骤中,农用车辆的主要任务是规划路线,这是执行任何田间作业的先决条件,因此被选为构建和评估这一集成的用例。所开发的系统包括基于云的调度管理信息系统(FMIS)中的高级路线规划算法、与使用机器人操作系统(ROS)的农用车辆兼容的综合算法包,以及连接调度管理信息系统算法、相应用户界面和车辆的通信和计算单元(CCU)。其分析模块可提供有关 UGV 性能指标的宝贵信息,特别是工作距离、非工作距离、重叠区域和田间穿越效率等性能指标。该系统通过两辆机器人车在各种作业配置、田地特征和耕作系统(露地、连作、果园)中执行路线执行任务的情况进行了演示。案例研究显示,田间穿越效率的操作性能差异在 79.2% 到 93% 之间,而在实施系统的最佳路线规划功能时,田间效率最多可提高 9.5%。展示的结果表明,用户可以通过修改来更好地控制田间作业,以确保最佳的田间性能,而且用户可以对作业进行全面监督。
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Integrated Route-Planning System for Agricultural Robots
Within the transition from precision agriculture (task-specific approach) to smart farming (system-specific approach) there is a need to build and evaluate robotic systems that are part of an overall integrated system under a continuous two-way connection and interaction. This paper presented an initial step in creating an integrated system for agri-robotics, enabling two-way communication between an unmanned ground vehicle (UGV) and a farm management information system (FMIS) under the general scope of smart farming implementation. In this initial step, the primary task of route-planning for the agricultural vehicles, as a prerequisite for the execution of any field operation, was selected as a use-case for building and evaluating this integration. The system that was developed involves advanced route-planning algorithms within the cloud-based FMIS, a comprehensive algorithmic package compatible with agricultural vehicles utilizing the Robot Operating System (ROS), and a communicational and computational unit (CCU) interconnecting the FMIS algorithms, the corresponding user interface, and the vehicles. Its analytical module provides valuable information about UGVs’ performance metrics, specifically performance indicators of working distance, non-working distance, overlapped area, and field-traversing efficiency. The system was demonstrated via the implementation of two robotic vehicles in route-execution tasks in various operational configurations, field features, and cropping systems (open field, row crops, orchards). The case studies showed variability in the operational performance of the field traversal efficiency to be between 79.2% and 93%, while, when implementing the optimal route-planning functionality of the system, there was an improvement of up to 9.5% in the field efficiency. The demonstrated results indicate that the user can obtain better control over field operations by making alterations to ensure optimum field performance, and the user can have complete supervision of the operation.
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