基于多目标遗传算法的水陆两栖可变形机器人结构参数设计方法
Mechanism-parameters Design Method of an Amphibious Transformable Robot Based on Multi-objective Genetic Algorithm
查看参考文献19篇
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文摘
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水陆两栖可变形机器人是一种兼具变形能力与两栖环境适应能力的新型移动机器人。在其机构设计中,结构参数直接影响该机器人在任务环境中的各项机动性能。针对水陆两栖可变形机器人工作环境复杂性和任务多变性,提出一种基于多目标遗传算法的机器人结构参数设计方法,以得到该型机器人在两栖环境中的最优的综合性能。在水陆两栖可变形机器人陆地环境和水环境中运动学和动力学模型基础上,建立两栖环境中机器人的机动性能指标函数与结构参数的映射关系,并在此基础之上构建面向水陆两栖可变形机器人的结构参数设计的多目标优化问题。利用多目标遗传算法得到该多目标机构参数设计问题的Pareto最优解集,并且通过组合赋权方法确定各目标决策属性的权重,从Pareto最优解集中得到符合设计要求的水陆两栖可变形机器人的各项机构参数最优解,进而指导机器人最终结构参数设计。根据最终得到的结构参数研制出水陆两栖可变形机器人样机Amoeba-II,并在两栖环境下进行样机的各项性能试验,最终验证了基于多目标遗传算法的机器人结构参数设计方法的有效性以及在机器人设计中的适用性。 |
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其他语种文摘
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As a new style of the mobile robot,the amphibious transformable robot can not only perform reconfiguration but also implement tasks in amphibious environment.For the mechanism design of the robot,the parameter of the mechanism takes influence on the robot’s performance in the task environment.To implement the performance optimization in the complex environment and task,a mechanism-parameters design method of an amphibious transformable robot based on multi-objective genetic algorithm is proposed.Based on the kinematics and dynamic analysis of the robot,the multi-objective optimization problem of the mechanism parameters design is established on the mapping relationships between the performance indexes and the mechanism parameters.The non-dominated sorting genetic algorithm II(NSGA-II) is adopted to solve this optimization problem and get the Pareto optimization.A solution of optimization problem of the mechanism parameters is extracted through the Pareto optimization based on the optimizing method of combination weighting of multi-attribute decision-making,and then the result is used to direct the mechanism design of the amphibious transformable robot,Amoeba-II.The experiment for the maneuverability of Amoeba-II in the amphibious environment is performed to certify the validity and applicability of the mechanism-parameters design method of amphibious transformable robot based on multi-objective genetic algorithm. |
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来源
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机械工程学报
,2012,48(17):10-20 【核心库】
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DOI
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10.3901/jme.2012.12.010
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关键词
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多目标遗传算法
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水陆两栖可变形机器人
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结构参数
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Pareto最优化
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地址
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中国科学院沈阳自动化研究所, 机器人学国家重点实验室, 沈阳, 110016
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语种
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中文 |
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ISSN
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0577-6686 |
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学科
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自动化技术、计算机技术 |
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基金
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国家自然科学基金资助项目
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文献收藏号
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CSCD:4642449
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