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Novel integrated optimization algorithm for trajectory planning of robot manipulators based on integrated evolutionary programming

机译:基于集成进化规划的机器人机械手轨迹规划集成优化算法

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Optimal trajectory planning for robot manipulators plays an important role in implementing the high productivity for robots.The performance indexes used in optimal trajectory planning are classified into two main categories:optimum traveling time and optimum mechanical energy of the actuators.The current trajectory planning algorithms are designed based on one of the above two performance indexes.So far,there have been few planning algorithms designed to satisfy two performance indexes simultaneously.On the other hand,some deficiencies arise in the existing integrated optimization algorithms of trajectory planning.In order to overcome those deficiencies,the integrated optimization algorithms of trajectory planning are presented based on the complete analysis for trajectory planning of robot manipulators.In the algorithm,two object functions are designed based on the specific weight coefficient method and "ideal point" strategy.Moreover,based on the features of optimization problem,the intensified evolutionary programming is proposed to solve the corresponding optimization model.Especially,for the Stanford Robot,the high-quality solutions are found at a lower cost.
机译:机器人操纵器的最佳轨迹规划在实现机器人的高生产率方面发挥着重要作用。最佳轨迹规划中使用的性能指标分为两个主要类别:最佳行驶时间和执行器的最佳机械能。当前的轨迹规划算法是基于上述两个性能索引的一个设计。因此,旨在同时满足两个性能指标的规划算法很少。另一方面,在轨迹规划的现有综合优化算法中出现了一些缺陷。为了克服这些缺陷,基于机器人操纵器的轨迹规划的完整分析,提出了轨迹规划的集成优化算法。在算法中,基于特定权重系数和“理想点”策略,设计了两个对象功能。关于优化问题的特征,建议提出强化进化编程来解决相应的优化模型。对于斯坦福机器人,高质量的解决方案以较低的成本找到。

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