Unidad Ejecutora Doble Dependencia - Universidad Nacional de San Juan, Facultad de Ingeniería - Consejo Nacional de Investigaciones Científicas y Técnicas

Publicaciones

Publicaciones en revistas, libros y congresos nacionales e internacionales.

Publicaciones 2019


El INAUT, como fruto de sus investigaciones y desarrollos, tiene una producción importante de publicaciones en revistas libros y congresos tanto nacionales como internacionales.


Revista Internacional con Referato

Admittance Controller with Spatial Modulation for Assisted Locomotion using a Smart Walker

Autores
Mario F. Jiménez ; Monllor, M.; Frizera Neto, A.; Freire Bastos, T.; Roberti, F.; Carelli, R.;


Resumen:
Smart Walkers are robotic devices that may be used to improve the stability in people with lower limb weakness or poor balance. Such devices may also offer support for cognitive disabilities and for people that cannot safely use conventional walkers. This paper presents an admittance controller that generates haptic signals to induce the tracking of a predetermined path. During use, when deviating from such path, the method proposed here varies the damping parameter of an admittance controller by means of a spatial modulation technique, resulting in a haptic feedback, which is perceived by the user as a difficult locomotion in wrong direction. The UFES’s Smart Walker uses a multimodal cognitive interaction composed by a haptic feedback, and a visual interface with two LEDs to indicate the correct/desired direction when necessary. The controller was validated in two experiments. The first one consisted of following a predetermined path composed of straight segments. The second experiment consisted of finding a predetermined path starting from a position outside of such path. When haptic feedback was used, the kinematic estimation error was around 0.3 (±0.13) m and the force applied to move the walker was approximately 5 kgf . When the multimodal interaction was performed with the haptic and visual interfaces, the kinematic estimation error decreased to 0.16 (±0.03) m, and the force applied dropped to around 1 kgf , which can be seen as an important improvement on assisted locomotion.

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Identification and adaptive PID Control of a hexacopter UAV based on neural networks

Autores
Rosales, C.; Soria, C.; Rossomando, F.;


Resumen:
In this paper, a novel adaptive PID controller for trajectory‐tracking tasks is proposed. It is implemented in discrete time over a hexacopter, and it takes into consideration the unmanned aerial vehicles (UAVs) nonlinear model. The PID controller is developed following an adaptive neural technique, and its stability is verified by the Lyapunov discrete theory. Besides, the neural identification of the dynamic model of the UAV is presented to backpropagate output errors to adjust PID gains with the purpose of reducing the control errors. The validation of the proposed algorithm is performed through experimental results with a hexacopter.

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Human-inspired stable bilateral teleoperation of mobile manipulators

Autores
Santiago, D.; Slawiñski, E.; Mut, V.;


Resumen:
This paper presents a novel strategy for delayed bilateral teleoperation of mobile manipulator robots. The strategy is based on the hypothesis that if the slave robot behaves similarly as the operator would do to the same task, the operator’s perception of the system states improves, and therefore the performance of the task is better. The proposed scheme allows controlling in simultaneously the mobile platform and the manipulator robot employing a single master device and maintaining the stability of the system against variable and asymmetric communication time delays. Stability guidelines based on Lyapunov Krasovskii method are provided for the adjustment of the delayed system. Besides, a new control allocation strategy is proposed founded on the study of human movement in a task of navigation-pick and place. Finally, the performance of the proposal is compared with the standard switched control using a real robotic platform. As a result in practice, the proposed scheme is easier and more intuitive for the operator, besides it allows to reduce significantly the time necessary to complete the task

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Force and Position-Velocity Coordination for Delayed Bilateral Teleoperation of a Mobile Robot

Autores
Slawiñski, E.; Moya González, V.; Santiago, D.; Mut, V.;


Resumen:
This document proposes a control scheme for delayed bilateral teleoperation of a mobile robot, which it is sought to achieve a coordination of the master device position with the slave mobile robot velocity, and at the same time synchronize the force exerted by the operator with force applied by the environment over the mobile robot. This approach allows the operator to improve the sensitive perception of the remote environment in which the robot navigates while he generates commands to control the mobile robot motion. In this paper, variable and asymmetrical communication time delays are taken into account, as well as a non-passive model of the human operator, for which a novel model is proposed that has a more general structure than the typical ones used to date in the teleoperation field. Furthermore, based on the theoretical analysis presented, the state of convergence in the stationary response is obtained. In addition, an experimental performance evaluation is carried out, where the position?velocity error, force error and the time to complete the task are evaluated. In the tests, a human operator commands a remote mobile robot to push objects of different weight while he perceives the weight of each object through the force feedback system. As an outcome, the theoretical and practical results obtained allow concluding that a satisfactory trade-off between stability and transparency is reached.

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Continuous Probabilistic SLAM solved via Iterated Conditional Modes

Autores
Gimenez, J.; Amicarelli, A.; Toibero, M.; di Sciascio, F.; Carelli, R.;


Resumen:
This article proposes a SLAM (Simultaneous Localization and Mapping) version with continuous probabilistic mapping (CP-SLAM), i.e., an algorithm of simultaneous localization and mapping that avoids the use of grids, and thus, does not require a discretized environment. A Markov Random Field (MRF) is considered to model this SLAM version with high spatial resolution maps. The mapping methodology is based on a point cloud generated by successive observations of the environment, which is kept bounded and representative by including a novel recursive subsampling method. The CP-SLAM problem is solved via Iterated Conditional Modes (ICM), which is a classic algorithm with theoretical convergence over any MRF. The probabilistic maps are the most appropriate to represent dynamic environments, and can be easily implemented in other versions of the SLAM problem, such as the multi-robot version. Simulations and real experiments show the flexibility and excellent performance of this proposal.

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An Adaptive Dynamic Controller for Quadrotor to Perform Trajectory Tracking Tasks

Autores
Paes Santos, M.; Rosales, C.; Sarapura, J.; Sarcinelli-Filho, M.; Carelli, R.;


Resumen:
This work proposes an adaptive dynamic controller to guide an unmanned aerial vehicle (UAV) when accomplishing trajectory tracking tasks. The controller structure consists of a kinematic controller that generates reference commands to a dynamic compensator in charge of changing the reference commands according to the system dynamics. The final control actions thus generated are then sent to the UAV to make it to track an arbitrary trajectory in the 3D space. The parameters of the dynamic compensator are directly updated during navigation, configuring a directly updated self-tuning regulator with input error, aiming at reducing the tracking errors, thus improving the system performance in task accomplishment. After describing the control system thus designed, its stability is proved using the Lyapunov theory. To validate the proposed system simulations and real experiments were run, some of them are reported here, whose results demonstrate the effectiveness of the proposed control system and its good performance, even when the initial values of the parameters associated to the dynamic model of the UAV are completely unknown. One of the conclusions, regarding the results obtained, is that the proposed system can be used as if it were an on-line identification subsystem, since the parameters converge to values that effectively represent the UAV dynamics.

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Congreso Internacional con Referato

Inertial Measurement System for Upper Limb Joints Tracking

Autores
Lopez, N.;Marcos Dominguez ; Orosco, E.;


Resumen:
This work presents a system for tracking and analysis of upper limb movement through the use of inertial sensors. The designed system uses four inertial sensors, which are placed at the midpoint of the corresponding segments, that is, hand, forearm, arm, and the last one is located between the scapulae and the spine, and between vertebrae T5 and T6 (Thoracic 5 and Thoracic 6). This last sensor is used as a reference point. The information of the four sensors is preprocessed by a microcontroller and sent wirelessly to a computer. The data of each sensor is processed in order to calculate the angular position of each joint. In this work the concept of quaternions is used to avoid the singularities that occur when the reference axes are aligned with the Earth’s gravity axis, instead of working directly with the representation through Euler angles. In addition, a descending gradient filter is implemented to merge the accelerometer and gyroscope data in order to compensate drift errors. To visualize the movement, a simple virtual environment is implemented with SimMechanics®. The designed system is evaluated with 10 volunteers, in flexo-extension and abduction-adduction movements, at different velocities and compared with goniometer measures. The system demonstrates good repeatability and the computed error was less than 3°.

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