Metodología de diseño de robots de asistenciales. Aplicación al robot portátil ASIBOT

El envejecimiento extraordinario de la población provoca la necesidad de desarrollar ayudas técnicas que asistan tanto a personas discapacitadas como a ancianos. Si bien el campo de la robótica asistencial lleva más de 25 años en desarrollo, todavía no se ha llegado a soluciones útiles y eficientes en cuanto al ratio beneficio-coste para el conjunto de la sociedad, y las actuales soluciones, se limitan a cubrir nichos de mercado.Esta tesis propone una metodología para el diseño de robots asistenciales, que a de partir de un equipo de diseño multidisciplinar e incluir a los usuarios en el proceso de diseño. Permite analizar, con enfoque global y no sólo científico, cómo influyen en la toma de decisiones los factores relacionados con el entorno, las tareas, el usuario y su seguridad. Plantea el diseño con el objetivo de desarrollar productos que llegan a todos y por tanto sean potencialmente económicos. La aplicación de esta metodología ha dado lugar al desarrollo de un sistema modular asistencial portátil, capaz de integrarse fácilmente en un entorno adaptado y de responder satisfactoriamente a las necesidades de un amplio espectro de personas con movilidad reducida. ___________________________________________Nowadays, the growing number of elderly people in today’s populations has created the need for developing some technical aids that helps disabled as well as elderly people. Although the field of rehabilitation robotics has been developing for over 25 years, still no useful efficient solutions have been achieved concerning the benefit-cost ratio for the general society, and the solutions that do exist are limited to certain specific market segments.This thesis proposes a methodology for the design of robotic assistant devices, from the creation of a multidisciplinary design team with the participation of the user, to the analysis of how the environment, tasks, users and safety issues, influence the decision making process using a scientific and also a humanistic point of view. The main goal of this methodology is to create robotic products which reach the all the market segments, thereby reducing the costs of these. The application of this methodology has led to the development of a portable assistance modular robot that can be easily integrated in to adapted environment and that responds to the special needs of a wide range of people

Generation and processing of simulated underwater images for infrastructure visual inspection with UUVs

The development of computer vision algorithms for navigation or object detection is one of the key issues of underwater robotics. However, extracting features from underwater images is challenging due to the presence of lighting defects, which need to be counteracted. This requires good environmental knowledge, either as a dataset or as a physic model. The lack of available data, and the high variability of the conditions, makes difficult the development of robust enhancement algorithms. A framework for the development of underwater computer vision algorithms is presented, consisting of a method for underwater imaging simulation, and an image enhancement algorithm, both integrated in the open-source robotics simulator UUV Simulator. The imaging simulation is based on a novel combination of the scattering model and style transfer techniques. The use of style transfer allows a realistic simulation of different environments without any prior knowledge of them. Moreover, an enhancement algorithm that successfully performs a correction of the imaging defects in any given scenario for either the real or synthetic images has been developed. The proposed approach showcases then a novel framework for the development of underwater computer vision algorithms for SLAM, navigation, or object detection in UUV

Functional evaluation of ASIBOT: A new approach on portable robotic system for disabled people

In this work, an innovative robotic solution for human care and assistance is presented. Our main objective is to develop a new concept of portable robot able to support the elderly and those people with different levels of disability during the execution of daily tasks, such as washing their face or hands, brushing their teeth, combing their hair, eating, drinking, and bringing objects closer, among others. Our prototype, ASIBOT, is a five degrees of freedom (DOF) self-contained manipulator that includes the control system and electronic equipment on board. The main advantages of the robot are its light weight, about 11 kg for a 1.3 m reach, its autonomy, and its ability to move between different points (docking stations) of the room or from the environment to a wheelchair and vice versa, which facilitates its supportive functions. The functional evaluation of ASIBOT is addressed in this paper. For this purpose the robotic arm is tested in different experiments with disabled people, gathering and discussing the results according to a methodology that allows us to assess users' satisfaction.The research leading to these results has received funding from the RoboCity2030- II-CM project (S2009/DPI-1559), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU.Publicad

The automated box and blocks test an autonomous assessment method of gross manual dexterity in stroke rehabilitation

Traditional motor assessment is carried out by clinicians using standard clinical tests in order to have objectivity in the evaluation, but this manual procedure is liable to the observer subjectivity. In this article, an automatic assessment system based on the Box and Blocks Test (BBT) of manual dexterity is presented. Also, the automatic test administration and the motor performance of the user is addressed. Through cameras RGB-D the execution of the test and the patient's movements are monitored. Based on colour segmentation, the cubes displaced by the user are detected and the traditional scoring is automatically calculated. Furthermore, a pilot trial in a hospital environment was conducted, to compare the automatic system and its e ectiveness with respect to the traditional one. The results support the use of automatic assessment methods of motor functionality, which in combination with robotic rehabilitation systems, could address an autonomous and objective rehabilitation process.The research leading to these results has received funding from the ROBOHEALTH-A project (DPI2013-47944-C4-1-R) funded by Spanish Ministry of Economy and Competitiveness and from the RoboCity2030-III-CM project (S2013/MIT-2748), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU

Task-oriented kinematic design of a symmetric assistive climbing robot

ASIBOT is an assistive climbing robot that is capable of aiding in daily tasks from fixed docking stations in the environment. A task-oriented design process was applied to improve the robot kinematic structure, which was based on the grid method. Twelve different robot designs were optimized for typical kitchen scenarios, followed by a quantitative comparison

An inverse kinematics problem solver based on screw theory for manipulator arms

[Abstract] Several methodologies exist for solving the inverse kinematics of a manipulator arm. Basing on screw theory, it is possible to efficiently obtain complete and exact solutions. An open-source C++ implementation of an automated problem solver of this kind is introduced, and a comparative with selected known algorithms is established using the TEO humanoid robot platform by Universidad Carlos III de Madrid. The Orocos Kinematics and Dynamics Library is used for geometry and motion-related operationsThe research leading to these results has received funding from: European project “Human Centric Algebraic Machine Learning” (ALMA), H2020-EIC-FETPROACT-2019; ROBOASSET, “Sistemas robóticos inteligentes de diagnóstico y rehabilitación de terapias de miembro superior”, PID2020-113508RB-I00 funded by AGENCIA ESTATAL DE INVESTIGACION (AEI); RoboCity2030-DIHCM, Madrid Robotics Digital Innovation Hub, S2018/NMT-4331, funded by “Programas de Actividades I+D en la Comunidad de Madrid” and cofunded by the European Social Funds (FSE) of the EU; the R&D&I project PLEC2021-007819 funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR; and cofounded by Structural Funds of the EU.Comunidad de Madrid; S2018/NMT-433

Humanoids. Los humanos y los robots cara a cara

Contiene: Entrevista con Santiago Martínez de la Casa, Investigador del Laboratorio de Robótica de la UC3M.-- Entrevista con Concepción Alicia Monje Micharet, Investigadora Laboratorio de Robótica de la UC3M.-- Entrevista con Alberto Jardón Huete, Investigador Laboratorio de Robótica de la UC3M

Object Detection Techniques Applied on Mobile Robot Semantic Navigation

The future of robotics predicts that robots will integrate themselves more every day with human beings and their environments. To achieve this integration, robots need to acquire information about the environment and its objects. There is a big need for algorithms to provide robots with these sort of skills, from the location where objects are needed to accomplish a task up to where these objects are considered as information about the environment. This paper presents a way to provide mobile robots with the ability-skill to detect objets for semantic navigation. This paper aims to use current trends in robotics and at the same time, that can be exported to other platforms. Two methods to detect objects are proposed, contour detection and a descriptor based technique, and both of them are combined to overcome their respective limitations. Finally, the code is tested on a real robot, to prove its accuracy and efficiency.The research leading to these results has received funding from the ARCADIA project DPI2010-21047-C02-01, funded by CICYT project grant on behalf of Spanish Ministry of Economy and Competitiveness and from the RoboCity2030-II project (S2009/DPI-1559), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU

3D exploration and navigation with optimal-RRT planners for ground robots in indoor incidents

Navigation and exploration in 3D environments is still a challenging task for autonomous robots that move on the ground. Robots for Search and Rescue missions must deal with unstructured and very complex scenarios. This paper presents a path planning system for navigation and exploration of ground robots in such situations. We use (unordered) point clouds as the main sensory input without building any explicit representation of the environment from them. These 3D points are employed as space samples by an Optimal-RRTplanner (RRT ∗ ) to compute safe and efficient paths. The use of an objective function for path construction and the natural exploratory behaviour of the RRT ∗ planner make it appropriate for the tasks. The approach is evaluated in different simulations showing the viability of autonomous navigation and exploration in complex 3D scenarios

ROS2 gesture classification pipeline towards gamified neuro-rehabilitation therapy

[Resumen] La rehabilitación es una herramienta esencial que ayuda a las personas a restaurar la movilidad en las extremidades afectadas por diversas afecciones, como enfermedades neurológicas. Las terapias convencionales, que incluyen terapia ocupacional, física y del habla, se han mejorado con nuevas tecnologías, como sistemas robóticos asistidos y juegos de realidad virtual y aumentada, para aumentar la participación y, en consecuencia, la efectividad. Esta investigación se centra en la implementación de un dispositivo portátil de sensores de electromiograma (EMG) de ocho canales, el brazalete Mindrove, para el reconocimiento de gestos. El objetivo es desarrollar un modelo clasificador utilizando el algoritmo de Máquinas de Vectores de Soporte (SVM) para distinguir ocho gestos diferentes de la mano y aplicarlo en un sistema de reconocimiento de gestos. El estudio demuestra la viabilidad de este sistema de reconocimiento y explora la aplicación potencial de esta tecnología en juegos interactivos de Unity para terapia de rehabilitación. Los resultados muestran una precisión prometedora en la clasificación del modelo y se necesita más investigación para abordar los desafíos relacionados con la especificidad del usuario y la precisión del reconocimiento de gestos. El trabajo futuro implica ampliar el repertorio de gestos reconocidos, incorporar datos adicionales del sensor y explorar técnicas de extracción de características más avanzadas para mejorar el rendimiento general del sistema de reconocimiento de gestos en terapias de rehabilitación.[Abstract] Rehabilitation is an essential tool that aids individuals in restoring mobility in limbs affected by various conditions, such as neurological diseases. Conventional therapies, including occupational, physical, and speech therapy, have been improved by new technologies, such as assistive robotic systems, along with virtual and augmented reality games, to enhance engagement and, consequently, effectiveness. This research focuses on implementing an eight-channel electromyogram (EMG) wearable sensor device, Mindrove armband, for gesture recognition. The objective is to develop a classifier model using the Support Vector Machine (SVM) algorithm to distinguish eight different hand gestures and apply it in a gesture recognition system. The study demonstrates the feasibility of this recognition system and explores the potential application of this technology in interactive Unity games for rehabilitation therapy. The results show promising accuracy in model classification, and further research is needed to address challenges related to user specificity and gesture recognition accuracy. Future work involves expanding the repertoire of recognized gestures, incorporating additional sensor data, and exploring more advanced feature extraction techniques to enhance the overall performance of the gesture recognition system in rehabilitation therapies.Ministerio de Ciencia e Innovación; PID2020-113508RBI0