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首页> 外文期刊>Current Organic Synthesis >Multirobot Routing Algorithms for Robots Operating in Vineyards
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Multirobot Routing Algorithms for Robots Operating in Vineyards

机译:用于葡萄园中运行的机器人的多机器人路由算法

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We consider the problem of multirobot routing in vineyards, a task motivated by our ongoing project aiming at creating a corobotic system to implement precision irrigation on large-scale commercial vineyards. The problem is related to a combinatorial optimization problem on graphs called "team orienteering." Team orienteering is known to be NP-hard, thus motivating the development of heuristic solutions that can scale to large problem instances. We propose three different parameter-free approaches informed by the domain we consider and compare them against a general purpose heuristic developed previously. In numerous benchmarks derived from data gathered in a commercial vineyard, we demonstrate that our solutions outperform the general purpose heuristic and are scalable, thus allowing us to solve instances with tens of thousands of vertices in the graphs. Note to Practitioners-Routing problems with budget and motion constraints are pervasive to many applications. In particular, the structural constraints considered in this problem are found not only in agricultural environments but also in warehouse logistics and other domains where goods are arranged along regular linear structures. This article proposes and analyzes algorithms that can be applied when multiple agents must be coordinated in these environments. In particular, by utilizing domain-specific knowledge, the solutions proposed in this article outperform general purpose approaches that poorly scale with the size of the environment. The algorithms we present also ensure that no collisions occur between robots-an aspect normally neglected in algorithms previously proposed to solve the team orienteering problem.
机译:我们考虑在葡萄园中的多机罗线路线的问题,这是我们正在进行的项目的任务,旨在创建一个有机型系统,以便在大型商业葡萄园实施精确灌溉。问题与名为“团队导向的联系”的组合优化问题有关。众所周知,我们队的队伍仍然是NP - 硬,从而激励了可以扩展到大问题实例的启发式解决方案的发展。我们提出了三种不同的无参数方法,我们考虑的域名通知,并将其与先前开发的通用启发式策略进行比较。在从商业葡萄园聚集的数据中派生的许多基准测试中,我们证明我们的解决方案优于通用启发式且可扩展,从而允许我们在图中解决数万个顶点的实例。注意对于许多应用程序来说,预算和运动约束的路由问题普遍存在。特别是,在这个问题中考虑的结构约束不仅在农业环境中发现,而且在仓库物流和货物沿规则的线性结构排列的其他领域中发现。本文提出并分析了在这些环境中必须协调的多个代理时可以应用的算法。特别是,通过利用域特定的知识,本文提出的解决方案优于与环境规模不大的通用方法。我们所呈现的算法还确保机器人之间不会发生碰撞 - 在先前提出以解决方向主问题的算法中通常忽略的一个碰撞。

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