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[ES] Un exoesqueleto robótico es un dispositivo electromecánico utilizado para aumentar la capacidad física de una persona, como ayuda a la locomoción o para procesos de rehabilitación de la marcha. En el caso de los exoesqueletos de rehabilitación se requiere que el sistema de control sea capaz de adaptarse adecuadamente a la evolución del paciente con el fin de optimizar su recuperación, esto implica el diseño de controladores robustos y precisos. En este trabajo se presenta el análisis cinemático, análisis dinámico y evaluación del sistema de control del exoesqueleto de rehabilitación ALICE. Dentro de las técnicas de control presentadas se encuentran: el controlador PD, PD adaptativo, y el controlador en modo deslizante. Además, se realiza un análisis de estabilidad utilizando el criterio de Lyapunov. Para probar el rendimiento de los reguladores, se utiliza un conjunto de datos de la Escuela de Fisioterapia de la ONCE de Madrid, correspondiente a personas sanas y personas con esclerosis múltiple. Se utiliza MATLAB como software de simulación y lenguaje de programación. [EN] A robotic exoskeleton is an electromechanical device that can be worn by a person to increase its physical capacity, to assist locomotion or for gait rehabilitation processes. In the case of rehabilitation exoskeletons, the control system is required to be smooth and capable to match accurately with the patients’ evolution in order to optimize the eciency of their recovery, this implies the design of robust and precise controllers. In this paper, kinematic analysis, dynamic analysis and control system evaluation for ALICE rehabilitation exoskeleton is presented. Among the control techniques used are: the PD controller, adaptive PD, and the sliding mode controller. In addition, a stability analysis using the Lyapunov criterion is performed. To test the performance of the controllers, gait data obtained by the ONCE School of Physiotherapy in Madrid, which correspond to healthy people and people with multiple sclerosis, are used. MATLAB as simulation software and programming language is used. Manuel Cardona agradece a la Fundación Carolina y a la Universidad Politécnica de Madrid, España, por el apoyo para la realización de esta investigación gracias a la beca de Doctorado otorgada en el marco del convenio con la Universidad Don Bosco, El Salvador.

This paper presents how the COVID-19 pandemic has changed the course of the mobile robotics market, showing the status of mobile robots in three stages: before, during and after the COVID-19 pandemic. By analyzing these stages, it is possible to estimate what awaits this market in the future. From the many applications of mobile robots found during the COVID- 19 pandemic, as will be shown later, it is clear that mobile robots will be an important part of the future influencing the accelerated growth of their market and development.

Objective: In this article, we present the conceptual development of a robotics platform, called ALICE (Assistive Lower Limb Controlled Exoskeleton), for kinetic and kinematic gait characterization. The ALICE platform includes a robotics wearable exoskeleton and an on-board muscle driven simulator to estimate the user’s kinetic parameters. Background: Even when the kinematics patterns of the human gait are well studied and reported in the literature, there exists a considerable intra-subject variability in the kinetics of the movements. ALICE aims to be an advanced mechanical sensor that allows us to compute real-time information of both kinetic and kinematic data, opening up a new personalized rehabilitation concept. Methodology: We developed a full muscle driven simulator in an open source environment and validated it with real gait data obtained from patients diagnosed with multiple sclerosis. After that, we designed, modeled, and controlled a 6 DoF lower limb exoskeleton with inertial measurement units and a position/velocity sensor in each actuator. Significance: This novel concept aims to become a tool for improving the diagnosis of pathological gait and to design personalized robotics rehabilitation therapies. Conclusion: ALICE is the first robotics platform automatically adapted to the kinetic and kinematic gait parameters of each patient. Peer reviewed

This paper describes the design and functioning by stages that compose the environmental and electric parameter recollecting device for research Purposes, energetic efficiency, that take place in the production of electric energy using a photovoltaic panel. The device has a local storage through an uSD memory card and remote cloud storage. The device is classified as an IoT device. The information can be accessed through a mobile app. It has temperature, UV rays, light, current, voltage and power sensors. A prototype of the device has been constructed and the results of this prototype are shown in a display and the electric variables were compared using a calibrated multimeter.