Antonio Besa

Kinematic description of soft tissue artifacts: quantifying rigid versus deformation components and their relation with bone motion

This paper proposes a kinematic approach for describing soft tissue artifacts (STA) in human movement analysis. Artifacts are represented as the field of relative displacements of markers with respect to the bone. This field has two components: deformation component (symmetric field) and rigid motion (skew-symmetric field). Only the skew-symmetric component propagates as an error to the joint variables, whereas the deformation component is filtered in the kinematic analysis process. Finally, a simple technique is proposed for analyzing the sources of variability to determine which part of the artifact may be modeled as an effect of the motion, and which part is due to other sources. This method has been applied to the analysis of the shank movement induced by vertical vibration in 10 subjects. The results show that the cluster deformation is very small with respect to the rigid component. Moreover, both components show a strong relationship with the movement of the tibia. These results suggest that artifacts can be modeled effectively as a systematic relative rigid movement of the marker cluster with respect to the underlying bone. This may be useful for assessing the potential effectiveness of the usual strategies for compensating for STA.

Analytical study of the effects of soft tissue artefacts on functional techniques to define axes of rotation

The accurate location of the main axes of rotation (AoR) is a crucial step in many applications of human movement analysis. There are different formal methods to determine the direction and position of the AoR, whose performance varies across studies, depending on the pose and the source of errors. Most methods are based on minimizing squared differences between observed and modelled marker positions or rigid motion parameters, implicitly assuming independent and uncorrelated errors, but the largest error usually results from soft tissue artefacts (STA), which do not have such statistical properties and are not effectively cancelled out by such methods. However, with adequate methods it is possible to assume that STA only account for a small fraction of the observed motion and to obtain explicit formulas through differential analysis that relate STA components to the resulting errors in AoR parameters. In this paper such formulas are derived for three different functional calibration techniques (Geometric Fitting, mean Finite Helical Axis, and SARA), to explain why each technique behaves differently from the others, and to propose strategies to compensate for those errors. These techniques were tested with published data from a sit-to-stand activity, where the true axis was defined using bi-planar fluoroscopy. All the methods were able to estimate the direction of the AoR with an error of less than 5°, whereas there were errors in the location of the axis of 30-40mm. Such location errors could be reduced to less than 17mm by the methods based on equations that use rigid motion parameters (mean Finite Helical Axis, SARA) when the translation component was calculated using the three markers nearest to the axis.

Design of a Dynamometric Wheel Rim

Dynamic simulation and advanced control are two areas that are becoming important in the field of design and industrial production. Dynamic simulation is a design tool now consolidated and commonly used in industries such as automobile and the related ones because it replaces the expensive tests with prototypes. Well, the results can provide simulation tools such as advanced control techniques critically depend on the quality of the data from which the mechanical model systems are generated. Direct measurement of these data or physical parameters (mass, location of centers of gravity, inertia tensors, friction parameters, etc) is problematic in systems that are being designed. We also have to consider that these parameters may change significantly over the life of the mechanical system. The alternative measurement is the identification of these parameters from experimental data acquired during the operation of mechanical systems. The actual proposal of this work is to design a wheel rim for light vehicle able to determinate the forces and moments that are transmitted to the axis of the vehicle wheel during use. The necessary instrumentation is designed using extensometry techniques, and the design process focuses on the study of the wheel rim deformations associated with the different forces acting on it. The study of strain performed on models analyzed by finite element techniques considering the different types of forces acting on the rim. Modeling the deformations behavior of the wheel rim, and doing a proper instrumentation based on the FEM analysis the results will be develop the procedure for the instrumentation of the rim to obtain the desired measurements.

Sequential and Simultaneous Algorithms to Solve the Collision-Free Trajectory Planning Problem for Industrial Robots – Impact of Interpolation Functions and the Characteristics of the Actuators on Robot Performance

Trajectory planning for robots is a very important issue in those industrial activities which have been automated. The introduction of robots into industry seeks to upgrade not only the standards of quality but also productivity as the working time is increased and the useless or wasted time is reduced. Therefore, trajectory planning has an important role to play in achieving these objectives (the motion of robot arms will have an influence on the work done). Formally, the trajectory planning problem aims to find the force inputs (control 憲岫建岻) to move the actuators so that the robot follows a trajectory 圏岫建岻 that enables it to go from the initial configuration to the final one while avoiding obstacles. This is also known as the complete motion planning problem compared with the path planning problem in which the temporal evolution of motion is neglected. An important part of obtaining an efficient trajectory plan lies with both the interpolation function used to help obtain the trajectory and the robot actuators. Ultimately actuators will generate the robot motion, and it is very important for robot behavior to be smooth. Therefore, the trajectory planning algorithms should take into account the characteristics of the actuators without forgetting the interpolation functions which also have an impact on the resulting motion. As well as smooth robot motion, it is also necessary to monitor some working parameters to verify the efficiency of the process, because most of the time the user seeks to optimize certain objective functions. Among the most important working parameters and variables are the time required to get the trajectory done, the input torques, the energy consumed and the power transmitted. The kinematic properties of the robot s links, such as the velocities, accelerations and jerks are also important. The trajectory algorithm should also not overlook the presence of possible obstacles in the workspace. Therefore it is very important to model both the workspace and the obstacles efficiently. The quality of the collision avoidance procedure will depend on this modelization.