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Agricultural service unit motion planning under harvesting scheduling and terrain constraints

机译:采伐计划和地形约束下的农业服务单位运动计划

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Most of the existing harvesting strategies rely on traditional path planners that only minimize the length of the path or energy consumption, ignoring the state of the crops and production process. Furthermore, the existing approaches use simplified kinematic models that neglect the robots' dynamics and their interaction with the terrain. To address these limitations, we propose and test in the field a harvesting and motion-planning strategy that explicitly considers the expected plant yield and the terrain's traversability. The latter has direct impact in the energy management of the agricultural service unit. A map with the predicted yield of each plant is employed to determine a priority queue of harvesting points. The priority queue, together with the harvesting rate and the robot's payload capacity, are used to generate a harvesting schedule for the different locations in the grove. The joint harvesting and motion-planning strategy applied is evaluated using field data from a Chilean avocado grove during the harvesting season. The results show that the proposed strategy provides a useful approach to automate the harvest points scheduling and motion planning while saving machinery resources.
机译:现有的大多数收割策略都依赖于传统的路径规划器,这些规划器仅将路径长度或能源消耗最小化,而忽略了作物的状态和生产过程。此外,现有的方法使用简化的运动学模型,而忽略了机器人的动力学及其与地形的相互作用。为了解决这些限制,我们在野外提出并测试了一种收割和运动计划策略,该策略明确考虑了预期的植物产量和地形的可穿越性。后者直接影响农业服务单位的能源管理。使用具有每种植物的预测产量的地图来确定收获点的优先队列。优先级队列以及收割率和机器人的有效负载容量,用于为树林中的不同位置生成收割时间表。在收获季节期间,使用来自智利鳄梨林的田间数据评估所采用的联合收获和运动计划策略。结果表明,所提出的策略提供了一种有用的方法,可以在节省机械资源的同时实现收割进度计划和运动计划的自动化。

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