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Combinatorial Optimization and Performance Analysis of a Multi-arm Cartesian Robotic Fruit Harvester-Extensions of Graph Coloring

机译:多臂笛卡尔机器人水果收割机的组合优化和性能分析-图形着色扩展

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摘要

A mobile melon robotic harvester consisting of multiple Cartesian manipulators, each with three degrees of freedom, is being developed. In order to design an optimal robot in terms of number of arms, manipulator capabilities, and robot speed, a method of allocating the fruits to be picked by each manipulator in a way that yields the maximum harvest has been developed. Such a method has already been devised for a multi-arm robot with 2DOF each. The maximum robotic harvesting problem was shown there to be an example of the maximum k-colorable subgraph problem (MKCSP) on an interval graph. However, for manipulators with 3DOF, the additional longitudinal motion results in variable intervals. To overcome this issue, we devise a new model based on the color-dependent interval graph (CDIG). This enables the harvest by multiple robotic arms to be modeled as a modified version of the MKCSP. Based on previous research, we develop a greedy algorithm that solves the problem in polynomial time, and prove its optimality using induction. As with the multi-arm 2DOF robot, when simulated numerous times on a field of randomly distributed fruits, the algorithm yields a nearly identical percentage of fruit harvested for given robot parameters. The results of the probabilistic analysis developed for the 2DOF robot was modified to yield a formula for the expected harvest ratio of the 3DOF robot. The significance of this method is that it enables selecting the most efficient actuators, number of manipulators, and robot forward velocity for maximal robotic fruit harvest.
机译:正在开发一种由多个笛卡尔操纵器组成的移动瓜机器人收获机,每个操纵器具有三个自由度。为了在臂数,机械手能力和机械手速度方面设计最佳机器人,已经开发了一种以产生最大收获的方式分配要由每个机械手采摘的水果的方法。已经针对每个具有2DOF的多臂机器人设计了这种方法。机器人最大收获问题显示为间隔图上最大k可着色子图问题(MKCSP)的示例。但是,对于具有3DOF的机械手,附加的纵向运动会导致可变的间隔。为了克服这个问题,我们设计了一个基于颜色的间隔图(CDIG)的新模型。这样就可以将多个机械手的收割建模为MKCSP的修改版本。在先前研究的基础上,我们开发了一种贪婪算法来解决多项式时间问题,并使用归纳法证明其最优性。与多臂2DOF机器人一样,在随机分布的水果场上进行多次仿真时,对于给定的机器人参数,该算法得出的水果收获百分比几乎相同。对2DOF机器人开发的概率分析结果进行了修改,以得出3DOF机器人的预期收获率的公式。此方法的意义在于,它可以选择最有效的执行器,机械手数量和机器人前进速度,以最大程度地收获机器人水果。

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