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A Robust Robotic Disassembly Sequence Design Using Orthogonal Arrays and Task Allocation

机译:使用正交数组和任务分配的鲁棒机器人拆卸序列设计

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Disassembly sequence planning (DSP) is a nondeterministic polynomial time (NP) complete problem, making the utilization of metaheuristic approaches a viable alternative. DSP aims at creating efficient algorithms for deriving the optimum or near-optimum disassembly sequence for a given product or a product family. The problem-specific nature of such algorithms, however, requires these solutions to be validated, proving their versatility in accommodating substantial variations in the problem environment. To achieve this goal, this paper utilizes Taguchi’s orthogonal arrays to test the robustness of a previously-proposed Simulated Annealing (SA) algorithm. A comparison with an exhaustive search is also conducted to verify the efficiency of the algorithm in generating an optimum or near-optimum disassembly sequence for a given product. In order to further improve the solution, a distributed task allocation technique is also introduced into the model environment to accommodate multiple robot arms.
机译:拆卸序列计划(DSP)是一个不确定的多项式时间(NP)完全问题,因此使用元启发式方法是一个可行的选择。 DSP旨在创建有效的算法,以得出给定产品或产品系列的最佳或近乎最佳的拆卸顺序。但是,此类算法的特定于问题的性质要求对这些解决方案进行验证,以证明其在适应问题环境中的实质性变化方面的多功能性。为了达到这个目标,本文利用田口的正交阵列来测试先前提出的模拟退火(SA)算法的鲁棒性。还进行了与详尽搜索的比较,以验证算法在生成给定产品的最佳或接近最佳拆卸顺序时的效率。为了进一步改进该解决方案,还将分布式任务分配技术引入到模型环境中以容纳多个机器人手臂。

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