Title :
Parameter identification for dynamic simulation
Author :
Joukhadar, A. ; Garat, A. ; Laugier, Ch.
Author_Institution :
Inst. Nat. de Recherche en Inf. et Autom., Montbonnot St. Martin, France
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 masses/springs based system (the RobotΦ system). This identification process is composed of two main steps: the first step consists in distributing the total mass of the object between the different particles while respecting the inertial properties of the object; the second one consists in finding the values of the physical parameters of the model such as elasticity, viscosity, plasticity, etc. A numerical solution of the first step is described, while a genetic algorithm based 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
Keywords :
Gaussian distribution; computational complexity; genetic algorithms; parameter estimation; robot dynamics; simulation; RobotΦ system; computation time; consistent behavior; dynamic simulation; elasticity; genetic algorithm based approach; masses/springs based system; parameter identification; plasticity; robots; viscosity; Computational modeling; Dynamic programming; Elasticity; Human robot interaction; Knee; Ligaments; Parameter estimation; Springs; Vehicle dynamics; Viscosity;
Conference_Titel :
Robotics and Automation, 1997. Proceedings., 1997 IEEE International Conference on
Conference_Location :
Albuquerque, NM
Print_ISBN :
0-7803-3612-7
DOI :
10.1109/ROBOT.1997.619070