Path Planning Algorithms for Automated Agricultural Machines Performing Sequentially Dependent Operations in Arable Farming

在耕作中执行顺序相关操作的自动化农业机械的路径规划算法

• 批准号: 528103308
• 负责人: Professor Dr.-Ing. Timo Oksanen
• 金额: --
• 依托单位: Lehrstuhl für Agrarmechatronik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/528103308?language=en
• 关键词: Path; Planning; Algorithms; Automated; Agricultural

This project focuses on developing computational coverage path planning algorithms for automated agricultural machines, including autonomous tractors. The main objective of this project is to study novel algorithms for the emerging problem of sequentially dependent agricultural robotic operations. Sequentially dependent means that one operation must be completed before the other. This problem arises especially in arable farming where several coverage operations are performed consecutively on the field during the cultivation cycle. Some of the operations, such as harrowing and seeding, can be performed immediately one after the other. The conventional way in arable farming is to perform only one operation at a time on the entire field. Several studies consider the problem where a single coverage operation such as seeding is divided among multiple machines, and the machines are working simultaneously on the same operation on the same field. A typical solution is to assign each machine their own workspace, allowing them to work independently without risk of conflicts or collisions. However, enabling the machines to perform different operations in parallel can reduce the total completion time of multiple operations, and therefore, improve the work efficiency. The goal of this project is to enable multiple machines to work on different operations simultaneously on essentially the same area of land without waiting for a previous operation to be finished on the entire field. This means that the simple solution of assigning each machine their individual, static workspace is infeasible. A significant part of the challenge is that the machines are heterogeneous, and oftentimes have different working widths. This means that one machine cannot simply follow another. The work in this project consists of deriving a formal definition of the sequentially dependent robotic problem, deriving an algorithmic solution to thereof, and finally, verifying and demonstrating the feasibility of the algorithm in real life with real agricultural machinery. To demonstrate the practical applicability of the results, this project includes empirical tests with real-life agricultural equipment, including tractors and implements for arable farming operations.

该项目致力于开发包括自动拖拉机在内的自动化农业机械的计算覆盖路径规划算法。该项目的主要目标是研究针对顺序依赖农业机器人作业这一新出现的问题的新算法。顺序依赖意味着一个操作必须在另一个操作之前完成。这一问题在耕地耕作中尤其突出，在耕作周期中，在田地上连续进行几次覆盖作业。一些手术，如犁和播种，可以一个接一个地立即进行。传统的耕作方式是一次只在整块田地上进行一次作业。一些研究考虑了这样一个问题，即一次覆盖作业(如播种)被分配给多台机器，而这些机器同时在同一块田地上进行相同的作业。典型的解决方案是为每台机器分配自己的工作空间，允许它们独立工作，而不会有冲突或冲突的风险。然而，使机器并行执行不同的操作可以减少多个操作的总完成时间，从而提高工作效率。该项目的目标是使多台机器能够在基本上相同的土地区域同时进行不同的作业，而不需要等待之前的作业在整个田地上完成。这意味着，为每台机器分配各自的静态工作空间的简单解决方案是不可行的。挑战的一个重要部分是，机器是不同的，而且经常具有不同的工作宽度。这意味着一台机器不能简单地跟随另一台机器。该项目的工作包括推导出序列相关机器人问题的形式化定义，推导出其算法解，最后用真实的农业机械验证和演示该算法在现实生活中的可行性。为了证明结果的实际适用性，该项目包括使用现实生活中的农业设备进行的经验测试，包括用于耕作作业的拖拉机和机具。