{"title":"Constrain-based identification of a dynamic model","authors":"A. Joukhadar, F. Garat, C. Laugier","doi":"10.1109/IROS.1997.649075","DOIUrl":null,"url":null,"abstract":"Dynamic simulation is potentially a powerful tool for studying complex contact interactions between robots and their environments. One of the main problems of such a simulation is the determination of the model parameters which provide realistic behavior for objects. This paper describes how to identify such parameters for a mass/spring based system. This identification process is composed of two main steps: 1) distributing the total mass of the object between different particles while respecting the inertial properties of the object; and 2) finding the values of the physical parameters of the model such as elasticity, viscosity, plasticity, etc. The numerical solution of the first step is described, while a genetic algorithm base approach is proposed for the second step. This approach allows us to find the values of the parameters which provide a consistent behavior under a set of given constraints (position, velocity, volume, etc.). It also allows us to minimize the computation time and to attach priorities with these constraints.","PeriodicalId":408848,"journal":{"name":"Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Innovative Robotics for Real-World Applications. IROS '97","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Innovative Robotics for Real-World Applications. IROS '97","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS.1997.649075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Dynamic simulation is potentially a powerful tool for studying complex contact interactions between robots and their environments. One of the main problems of such a simulation is the determination of the model parameters which provide realistic behavior for objects. This paper describes how to identify such parameters for a mass/spring based system. This identification process is composed of two main steps: 1) distributing the total mass of the object between different particles while respecting the inertial properties of the object; and 2) finding the values of the physical parameters of the model such as elasticity, viscosity, plasticity, etc. The numerical solution of the first step is described, while a genetic algorithm base approach is proposed for the second step. This approach allows us to find the values of the parameters which provide a consistent behavior under a set of given constraints (position, velocity, volume, etc.). It also allows us to minimize the computation time and to attach priorities with these constraints.
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基于约束的动态模型识别
动态仿真是研究机器人与其环境之间复杂接触相互作用的有力工具。这种仿真的主要问题之一是确定模型参数,以提供对象的真实行为。本文描述了如何识别基于质量/弹簧的系统的这些参数。该识别过程由两个主要步骤组成:1)在尊重物体惯性特性的情况下,将物体的总质量分配给不同的粒子;2)求出模型的弹性、粘度、塑性等物理参数的取值。给出了第一步的数值求解方法,提出了基于遗传算法的第二步求解方法。这种方法允许我们找到在一组给定约束(位置、速度、体积等)下提供一致行为的参数值。它还允许我们最小化计算时间,并为这些约束附加优先级。
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