Xabier Iriarte

On the Experiment Design for Direct Dynamic Parameter Identification of Parallel Robots

Accurate robot dynamic models require the estimation and validation of the dynamic parameters through experiments. To this end, when performing the experiments, the system has to be properly excited so that the unknown parameters can be accurately estimated. The experiment design basically consists of optimizing the trajectory executed by the robot during the experiment. Due to the restricted workspace with parallel robots this task is more challenging than for serial robots; thus, this paper is focused on the experiment design aimed at dynamic parameter identification of parallel robots. Moreover, a multicriteria algorithm is proposed in order to reduce the deficiencies derived from the single-criterion optimization. The results of the identification using trajectories based on a single criterion and the multicriteria approaches are compared, showing that the proposed optimization can be considered as a suitable procedure for designing exciting trajectories for parameter identification.

Teaching Mechanism and Machine Theory with GeoGebra

Teaching Mechanism and Machine Theory involves the description of mechanisms which are not easy to represent with static drawings. Computer applications are a common way to reproduce the motion of mechanisms. GeoGebra is a free dynamic geometry software with interactive graphics that can help in this task. By introducing mathematical constraints, such as constant distances, intersections, tangency or perpendicularity, it is possible to build a wide range of interactive mechanisms. This software has been used at the Public University of Navarra on a Degree in Mechanical Engineering, having a successful experience with the students. The software has been used in two ways. On the one hand, some mechanisms have been prepared and shown to the students in theoretical lessons in order to explain their motion. On the other hand, practical lessons have been carried out, in which the students have programmed one degree of freedom mechanisms with GeoGebra.Students have shown interest in the practical lessons and results have been satisfactory.

Identification of dynamic parameters in low-mobility mechanical systems: application to short long arm vehicle suspension

The identification of dynamic parameters in low-mobility mechanical systems is addressed and applied to short long arm (SLA) front car suspension. The main goal of the identification technique is to obtain, from experimental measurements, the values of those dynamic parameters (masses, location of the centre of masses, terms of the inertial matrix of the links, constant friction terms and elastic and viscous damping constant terms) that affect the dynamic behaviour of the system. Moreover, additional but important information that could be obtained from the procedure is related to the weight of those terms inside the dynamics of the system, so that simplified dynamic models based on relevant and well-identified parameters can be established. First, a systematic procedure will be presented for obtaining the equations of motion in a linear form with regard to the dynamic parameters to be identified. The main drawbacks related to the identification of parameters in low-mobility mechanisms will be pointed out, mainly the difficulty of determining a natural cutoff point into the singular values of the observation matrix which allows us to determine the true dimension of the set of base parameters and of obtaining an observation matrix well conditioned from the numerical point of view that allows an identification in the presence of measurement error. The procedure proposed for overcoming these problems will be based on the development of symbolic relationships among the physical parameters in order to determine the true rank of the observation matrix and on the consideration of a reduced subset of the base parameters set. These relevant parameters will be selected according to their influence on the dynamic behaviour of the mechanical system. A virtual benchmark will be used for testing purposes. The dynamic models based on relevant parameters show a better adjustment than the complete ones, mainly when the level of noise in the measurements used in the identification process increases.

Real-Time Hardware-in-the-Loop Simulation of a Hexaglide Type Parallel Manipulator on a Real Machine Controller

The deployment of a virtual implementation of a Hexaglide type parallel robot in the LinuxCNC machine controller running on RTAI RT Linux is presented and assessed. This HiL simulation is used to safely test different experiments and control algorithms before deploying them on the real system. State of the art algorithms to efficiently perform Real-Time system’s state integration are presented. The symbolic library LIB3D_MEC-GiNaC has been used to generate and adapted to automatically export the matrices required by the different algorithms. Three different parametrization strategies are implemented and compared. Performance improvement due to optimization by atomization are also reported. Excellent (under 10 − 5 s) Real-Time performance is achieved on standard off the shelf hardware.

Dynamic Parameter Identification in the Front Suspension of a Vehicle: On the Influence of Different Base Parameter Sets

This paper addresses the identification of the inertial parameters of a dynamic front suspension. The concept of inertia and mass transfer is used to obtain three different sets of base parameters, reducing them to the relevant parameters through the analysis of dynamic contribution. These models are compared with two models obtained by numerical methods, which have no physical meaning. The evaluation is performed by crossing data with different trajectories to those used in the identification process. The results show that the use of inertia and mass transfer in the selection of potential base parameters generates well-conditioned models that are very close to the original model behavior.

Kinematic Design of a New Four Degree-of-Freedom Parallel Robot for Knee Rehabilitation

This work was funded by the Plan Nacional de I + D, Comision Interministerial de Ciencia y Tecnologia (FEDER-CICYT) under the projects DPI2013-44227-R and DPI2017-84201-R.

Teaching Shaft Balancing as a Parameter Estimation Problem

One of the typical topics on Mechanisms and Machine Theory subject is shaft or rotor balancing. The unbalance is produced by an inadequate mass distribution of the rotating part. It can be said that static unbalance exists when the mass centre does not lie on the rotation axis and that dynamic unbalance happens when the rotating axis is not a principal inertia axis of the shaft. Making use of this point of view, the way to correct an unbalanced shaft is to cancel its inertia products involving the rotation axis. If these inertia products are known, it is easy to calculate the mass to be added or eliminated in order to cancel them. Instead, if the inertia products are unknown, they must be experimentally estimated in order to balance the shaft. This work presents a way to balance an unknown shaft as a parameter estimation problem. The formulation of least-square parameter estimation has been used in order to estimate the inertial properties of a shaft. Then, the balancing of the shaft is easily carried out. This approach has been explained to students of a Degree on Mechanical Engineering at the Public University of Navarra. By means of a virtual model of an unbalanced shaft, students have estimated the inertial properties of the unbalanced shaft and then calculated the masses to be added in order to balance it. I has been a satisfactory experience in order to improve the students skills on the Mechanism and Machine Theory and they have also learned a formulation that can be used for other kind of problems.

A Multicriteria Approach for Optimal Trajectories in Dynamic Parameter Identification of Parallel Robots

When dealing with the development of accurate robot dynamic models, the estimation and validation of the dynamic parameters through experiments becomes necessary. One of the most important objectives to achieve in the design of the experiment, aimed at identification, is to properly excite the system so that the unknown parameters can be accurately estimated. It is customary to find proper excitations optimizing the observation matrix of the model w.r.t. a certain criterion. In this paper the suitability of some trajectory optimization criteria are evaluated for parallel robots. Moreover, a multicriteria algorithm is proposed in order to reduce the deficiencies derived from the single criterion optimization.