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首页> 外文期刊>Computers and Electronics in Agriculture >Multi-objective path planner for an agricultural mobile robot in a virtual greenhouse environment
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Multi-objective path planner for an agricultural mobile robot in a virtual greenhouse environment

机译:虚拟温室环境中农业移动机器人的多目标路径规划师

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Robotics in agriculture has experienced enormous development in the past decade. In order to accomplish numerous agricultural tasks, the order in which the crop is covered is particularly important in order to minimise travelling cost and to preserve soil conditions. However, it is difficult to determine an optimised sequential path for the robot which minimizes navigation costs, while ensuring a fully completed agricultural operation. This paper presents the implementation of a multi-objective algorithm to solve the path planning problem for pesticide spraying operation inside a greenhouse. Pesticide spraying problems found in greenhouses have been adapted from the vehicle routing problem found in operations research, where the infected plants represent the customers and the mobile robot represents the vehicles. Routes between the plants are generated using a Probabilistic Roadmap path planner based on the designed virtual environment. The virtual environment is designed based on the real greenhouse environment to visualise the agricultural operation inside the greenhouse. To determine the best routes for the mobile robot, the Non-dominated Sorting Genetic Algorithm using Reference Point Based (NSGA-III) is tested and applied to the system. The solution quality has been compared with the Non-dominated Sorting Genetic Algorithm (NSGA-II) using the C-metric indicator. Comparisons with NSGA-II using the C-metric indicator verify that NSGA-III offers a superior performance with a good quality result.
机译:农业机器人在过去十年中经历了巨大的发展。为了实现许多农业任务,涵盖作物的顺序尤为重要,以便最大限度地减少旅行成本并保持土壤条件。然而,难以确定机器人的优化连续路径,这使导航成本最大限度地减少了导航成本,同时确保完全完成的农业操作。本文介绍了多目标算法,解决温室内农药喷涂运行的路径规划问题。在温室中发现的农药喷洒问题已经改编自运营研究中的车辆路由问题,其中受感染的植物代表客户,移动机器人代表车辆。植物之间的路线是使用基于设计的虚拟环境的概率路线图路径规划生成的。虚拟环境是根据真正的温室环境设计的,以便在温室内可视化农业操作。为了确定移动机器人的最佳路线,测试使用基于参考点(NSGA-III)的非主导排序遗传算法并应用于系统。使用C-Mentric指标指示器与非主导分类遗传算法(NSGA-II)进行比较了溶液质量。使用C-Metric指示符的NSGA-II比较验证NSGA-III提供优质的性能,质量良好。

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