SYMORO+: A SYSTEM FOR THE SYMBOLIC MODELLING OF ROBOTS

International audienceThis paper presents the software package SYMORO+ for the automatic symbolic modelling of robots. This package permits to generate the direct geometric model, the inverse geometric model, the direct kinematic model, the inverse kinematic model, the dynamic model, and the inertial parameters identification models. The structure of the robots can be serial, tree structure or containing closed loops. The package runs on Sun stations and PC computers, it has been developed under MATHEMATICA and C language. In this paper we give an overview of the algorithms used in the different models, the computational cost of the dynamic models of the PUMA robot are given

On the simulation of space based manipulators with contact

An efficient method of simulating the motion of space based manipulators is presented. Since the manipulators will come into contact with different objects in their environment while carrying out different tasks, an important part of the simulation is the modeling of those contacts. An inverse dynamics controller is used to control a two armed manipulator whose task is to grasp an object floating in space. Simulation results are presented and an evaluation is made of the performance of the controller

Dynamics Modeling of Structure-Varying Kinematic Chains for Free-Flying Robots

2008 IEEE International Conference on Robotics and Automation Pasadena, CA, USA, May 19-23, 200

Global Identification of Drive Gains and Dynamic Parameters of Parallel Robots - Part 2: Case Study

International audienceUsually, identification models of parallel robots are simplified and take only the dynamics of the moving platform into account. Moreover the input efforts are estimated through the use of the manfucaturer's actuator drive gains that are not calibrated thus leading to identification errors. In this paper a systematic way to derive the full dynamic identification model of the Orthoglide parallel robot in combination with a method that allows the identification of both robot inertial parameters and drive gains

Global Identification of Joint Drive Gains and Dynamic Parameters of Parallel Robots

International audienceOff-line robot dynamic identification methods are based on the use of the Inverse Dynamic Identification Model (IDIM), which calculates the joint forces/torques (estimated as the product of the known control signal-the input reference of the motor current loop-with the joint drive gains) that are linear in relation to the dynamic parameters, and on the use of linear least squares technique to calculate the parameters (IDIM-LS technique). Most of the papers dealing with the dynamic parameters identification of parallel robots are based on simple models, which take only the dynamics of the moving platform into account. However, for advanced applications such as output force control in which the robot interaction force with the environment are estimated from the values of the input reference, both identifications of the full robot model and joint drive gains are required to obtain the best results. In this paper a systematic way to derive the full dynamic identification model of parallel robots is proposed in combination with a method that allows the identification of both robot inertial parameters and drive gains. The method is based on the total least squares solution of an over-determined linear system obtained with the inverse dynamic model. This model is calculated with available input reference of the motor current loop and joint position sampled data while the robot is tracking some reference trajectories without load on the robot and some trajectories with a known payload fixed on the robot. The method is experimentally validated on a prototype of parallel robot, the Orthoglide

SICOMAT : a system for SImulation and COntrol analysis of MAchine Tools

International audienceThis paper presents a software package for the simulation and the control analysis of machine tool axes. This package which is called SICOMAT (SImulation and COntrol analysis of MAchine Tools), provides a large variety of toolboxes to analyze the behavior and the control of the machine. The software takes into account several elements such as the flexibility of bodies, the interaction between several axes, the effect of numerical control and the availability to reduce models

Trajectory Synthesis for Fisher Information Maximization

Estimation of model parameters in a dynamic system can be significantly improved with the choice of experimental trajectory. For general, nonlinear dynamic systems, finding globally "best" trajectories is typically not feasible; however, given an initial estimate of the model parameters and an initial trajectory, we present a continuous-time optimization method that produces a locally optimal trajectory for parameter estimation in the presence of measurement noise. The optimization algorithm is formulated to find system trajectories that improve a norm on the Fisher information matrix. A double-pendulum cart apparatus is used to numerically and experimentally validate this technique. In simulation, the optimized trajectory increases the minimum eigenvalue of the Fisher information matrix by three orders of magnitude compared to the initial trajectory. Experimental results show that this optimized trajectory translates to an order of magnitude improvement in the parameter estimate error in practice.Comment: 12 page

SICOMAT : a system for SImulation and COntrol analysis of MAchine Tools

International audienceThis paper presents a software package for the simulation and the control analysis of machine tool axes. This package which is called SICOMAT (SImulation and COntrol analysis of MAchine Tools), provides a large variety of toolboxes to analyze the behavior and the control of the machine. The software takes into account several elements such as the exibility of bodies, the interaction between several axes, the effect of numerical control and the availability to reduce models