Efren Gorrostieta

Development of a robotic FD-CT-guided navigation system for needle placement-preliminary accuracy tests.

A needle placement system using a serial robot arm for manipulation of biopsy and/or treatment needles is introduced. A method for fast calibration of the robot and the preliminary accuracy tests of the robotic system are presented.

A Fully Sensorized Cooperative Robotic System for Surgical Interventions

In this research a fully sensorized cooperative robot system for manipulation of needles is presented. The setup consists of a DLR/KUKA Light Weight Robot III especially designed for safe human/robot interaction, a FD-CT robot-driven angiographic C-arm system, and a navigation camera. Also, new control strategies for robot manipulation in the clinical environment are introduced. A method for fast calibration of the involved components and the preliminary accuracy tests of the whole possible errors chain are presented. Calibration of the robot with the navigation system has a residual error of 0.81 mm (rms) with a standard deviation of ±0.41 mm. The accuracy of the robotic system while targeting fixed points at different positions within the workspace is of 1.2 mm (rms) with a standard deviation of ±0.4 mm. After calibration, and due to close loop control, the absolute positioning accuracy was reduced to the navigation camera accuracy which is of 0.35 mm (rms). The implemented control allows the robot to compensate for small patient movements.

Neuro Fuzzy Modeling of Control Systems

The analysis of the models is carried out starting from experimental data of a multivariable system MISO (Many Input Single Output). The models’ implementation was made using fuzzy logic. In fuzzy logic, the cluster technique was used to decrease the number of rules to use in the identification. This technique is opposed to the conventional method which requires a considerable number of fuzzy inference rules to approach the model. In the consequence of fuzzy model, different techniques are used to implement Takagi-Sugeno type rules. By other hand, we implemented the Neuro-fuzzy modeling methods, which let represent the non-linear system and at the same time a system with some learning degree using different topologies. By comparison the goodness of each method is obtained.

Modeling and simulation methodology applied in the study case of the analysis of an anthropomorphic manipulator robot

This paper presents a novel modeling and simulation methodology applied in the study case of dynamic behavior analysis of a manipulator robot of three degree freedom, so to consider the full mathematical model of the manipulator it is possible to provide support for planning, design and evaluation of the robot, later, an evaluation of the control strategies is performed by adding a PD control with gravity torque compensation. The simulations are executed and it shows the compensation of the gravity effects during the point-to-point trajectory tracking, and therefore the validation of the methodology is done.

Modeling and simulation of the dynamic behavior applied to a mechatronic unit EOD/IEDD

This paper presents the modeling and simulation of a mechatronic unit EOD/IEDD [1] (explosive ordinance disposal/ improvised explosive device disposal), by carrying out a modeling and simulation of a proposed control, this unit is applied to perform hazardous-duty operations. In this work proposes a methodology to model and simulate the behavior of a mechatronic unit. The mechatronic unit is a mobile manipulator with 5 degrees of freedom. The simulation considers the dynamic of system coupled, such that the errors in the model can be detected and later confined by control.