A Model-Free Approach for Accurate Joint Motion Control in Humanoid Locomotion

A new model-free approach to precisely control humanoid robot joints is presented in this article. An input&-output online identification procedure will permit to compensate neglected or uncertain dynamics, such as, on the one hand, transmission and compliance nonlinear effects, and, on the other hand, network transmission delays. Robustness toparameter variations will be analyzed and compared to other advanced PID-based controllers. Simulations will show that not only good tracking quality can be obtained with this novel technique, but also that it provides a very robust behavior to the closed-loop system. Furthermore, a locomotion task will be tested in a complete humanoid simulatorto highlight the suitability of this control approach for such complex systems.This work has been supported by the CAM Project S2009/DPI-1559/ROBOCITY2030 II, developed by the research team RoboticsLab at the University Carlos III of Madrid.Publicad

Programa propio: incentivar la participación

Audiovisuales. Programa Propio de Investigación UC3M. Entrevista a Carlos Balaguer, vicerrector de Investigación y Transferencia de la Universidad. Disponible en: https://arcamm.uc3m.es/arcamm/?item=107efd2246dd7b321d6b4b1ca0ee8498 .-- Programa Propio de Investigación UC3M: Entrevista a Arturo Azcorra. Disponible en: https://arcamm.uc3m.es/arcamm/?item=e601e68dc5e5f5c208b5e651195dcc59El Vicerrectorado de Investigación y Transferencia cuenta con una serie de medidas y líneas de financiación, la mayoría encuadradas en el Programa Propio de Investigación (PPI). Con este programa se pretende fomentar la realización de actividades que se consideran estratégicas para la universidad, mediante la concesión, anualmente, de ayudas económicas que permitan financiar esas actividades y, así, promocionar la excelencia y la internacionalización de la actividad investigadora

New trends and challenges in the automatic generation of new tasks for humanoid robots

Proceeding of: RobCity16: Robots for citizens: Open Conference on Future Trends in Robotics, Madrid May 26-27 2016In this paper, the study and implementation of a task generation system that uses the information obtained from the user and already known cases is presented. One of the main objectives of the system is to introduce a new approach in robotics that takes into account the physical limitation of teaching and learning time, and thus the amount of knowledge that a robot can obtain of a given environment (tasks, objects, user preferences...), as a critical bottleneck of any robotic system. For this, the study of the Case Based Reasoning (CBR) problem is presented. Additionally, Base Trajec-tory Combination (BATC), a novel trajectory combination method based on a simplified CBR structure, using trajectories instead of high-level tasks, is proposed and explained. Finally, this system is tested with Move-it! as the simulation environment, using the humanoid robot TEO from Universidad Carlos III de Madrid as the robotic platform. The results of these experiments are also presented with the corresponding conclusions and future research lines.This research has received funding from the RoboCity2030-III-CM project (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos. Fase III; S2013/MIT-2748), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU

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

A new approach on human-robot collaboration with humanoid robot RH-2

This paper was originally submitted under the auspices of the CLAWAR Association. It is an extension of work presented at CLAWAR 2009: The 12th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines, Istanbul, Turkey.This paper presents a novel control architecture for humanoid robot RH-2. The main objective is that a robot can perform different tasks in collaboration with humans in working environments. In order to achieve this goal, two control loops have to be defined. The outer loop, called collaborative control loop, is devoted to the generation of stable motion patterns for a robot, given a specific manipulation task. The inner loop, called posture stability control loop, acts to guarantee the stability of humanoid for different poses determined by motion patterns. A case study is presented in order to show the effectiveness of the proposed control architecture.This work has been supported by the CAM Project S2009/DPI-1559/ROBOCITY2030 II, the CYCIT Project PI2004-00325 and the European Project Robot@CWE FP6-2005-IST-5

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

Sign Language Representation by TEO Humanoid Robot: End-User Interest, Comprehension and Satisfaction

In this paper, we illustrate our work on improving the accessibility of Cyber&-Physical Systems (CPS), presenting a study on human&-robot interaction where the end-users are either deaf or hearing-impaired people. Current trends in robotic designs include devices with robotic arms and hands capable of performing manipulation and grasping tasks. This paper focuses on how these devices can be used for a different purpose, which is that of enabling robotic communication via sign language. For the study, several tests and questionnaires are run to check and measure how end-users feel about interpreting sign language represented by a humanoid robotic assistant as opposed to subtitles on a screen. Stemming from this dichotomy, dactylology, basic vocabulary representation and end-user satisfaction are the main topics covered by a delivered form, in which additional commentaries are valued and taken into consideration for further decision taking regarding robot-human interaction. The experiments were performed using TEO, a household companion humanoid robot developed at the University Carlos III de Madrid (UC3M), via representations in Spanish Sign Language (LSE), and a total of 16 deaf and hearing-impaired participants.The research leading to these results has received funding from the RoboCity2030-III-CM project (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos. fase III; S2013/MIT-2748), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU

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

A study on machine vision techniques for the inspection of health personnels' protective suits for the treatment of patients in extreme isolation

The examination of Personal Protective Equipment (PPE) to assure the complete integrity of health personnel in contact with infected patients is one of the most necessary tasks when treating patients affected by infectious diseases, such as Ebola. This work focuses on the study of machine vision techniques for the detection of possible defects on the PPE that could arise after contact with the aforementioned pathological patients. A preliminary study on the use of image classification algorithms to identify blood stains on PPE subsequent to the treatment of the infected patient is presented. To produce training data for these algorithms, a synthetic dataset was generated from a simulated model of a PPE suit with blood stains. Furthermore, the study proceeded with the utilization of images of the PPE with a physical emulation of blood stains, taken by a real prototype. The dataset reveals a great imbalance between positive and negative samples; therefore, all the selected classification algorithms are able to manage this kind of data. Classifiers range from Logistic Regression and Support Vector Machines, to bagging and boosting techniques such as Random Forest, Adaptive Boosting, Gradient Boosting and eXtreme Gradient Boosting. All these algorithms were evaluated on accuracy, precision, recall and F1 score; and additionally, execution times were considered. The obtained results report promising outcomes of all the classifiers, and, in particular Logistic Regression resulted to be the most suitable classification algorithm in terms of F1 score and execution time, considering both datasets.The research leading to these results received funding from: Inspección robotizada de los trajes de proteccion del personal sanitario de pacientes en aislamiento de alto nivel, incluido el ébola, Programa Explora Ciencia, Ministerio de Ciencia, Innovación y Universidades (DPI2015-72015-EXP); the RoboCity2030-DIH-CM Madrid Robotics Digital Innovation Hub (“Robótica aplicada a la mejora de la calidad de vida de los ciudadanos. fase IV”; S2018/NMT-4331), funded by “Programas de Actividades I+D en la Comunidad de Madrid” and cofunded by Structural Funds of the EU; and ROBOESPAS: Active rehabilitation of patients with upper limb spasticity using collaborative robots, Ministerio de Economía, Industria y Competitividad, Programa Estatal de I+D+i Orientada a los Retos de la Sociedad (DPI2017-87562-C2-1-R)

A use case of an adaptive cognitive architecture for the operation of humanoid robots in real environments

Future trends in robotics call for robots that can work, interact and collaborate with humans. Developing these kind of robots requires the development of intelligent behaviours. As a minimum standard for behaviours to be considered as intelligent, it is required at least to present the ability to learn skills, represent skill's knowledge and adapt and generate new skills. In this work, a cognitive framework is proposed for learning and adapting models of robot skills knowledge. The proposed framework is meant to allow for an operator to teach and demonstrate the robot the motion of a task skill it must reproduce; to build a knowledge base of the learned skills knowledge allowing for its storage, classification and retrieval; to adapt and generate new models of a skill for compliance with the current task constraints. This framework has been implemented in the humanoid robot HOAP-3 and experimental results show the applicability of the approach.The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: The research leading to these results has received funding from the RoboCity2030-III-CM project (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos. Fase III; S2013/MIT-2748), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU