Bayesian Variable Selection with applications in health sciences

In health sciences, identifying the leading causes that govern the behaviour of a response variable is a question of crucial interest. Formally, this can be formulated as a variable selection problem. In this paper, we introduce the basic concepts of the Bayesian approach for variable selection based on model choice, emphasizing the model space prior adoption and the algorithms for sampling from the model space and for posterior probabilities approximation; and show its application to two common problems in health sciences. The first concerns a problem in the field of genetics while the second is a longitudinal study in cardiology. In the context of these applications, considerations about control for multiplicity via the prior distribution over the model space, linear models in which the number of covariates exceed the sample size, variable selection with censored data, and computational aspects are discussed. The applications presented here also have an intrinsic statistical interest as the proposed models go beyond the standard general linear model. We believe this work will broaden the access of practitioners to Bayesian methods for variable selection

Bayesian Variable Selection with Applications in Health Sciences

[EN] In health sciences, identifying the leading causes that govern the behaviour of a response variable is a question of crucial interest. Formally, this can be formulated as a variable selection problem. In this paper, we introduce the basic concepts of the Bayesian approach for variable selection based on model choice, emphasizing the model space prior adoption and the algorithms for sampling from the model space and for posterior probabilities approximation; and show its application to two common problems in health sciences. The first concerns a problem in the field of genetics while the second is a longitudinal study in cardiology. In the context of these applications, considerations about control for multiplicity via the prior distribution over the model space, linear models in which the number of covariates exceed the sample size, variable selection with censored data, and computational aspects are discussed. The applications presented here also have an intrinsic statistical interest as the proposed models go beyond the standard general linear model. We believe this work will broaden the access of practitioners to Bayesian methods for variable selection.SIMinisterio de Economía, Comercio y EmpresaThis work has been funded by the project PID2019-104790GB-I00 from the Ministerio de Ciencia e Innovación (Spain). The work of G. Garcia-Donato has been also supported by the project SBPLY/17/180501/000491 from the Consejeria de Educacion, Cultura y Deportes de la Junta de Comunidades de Castilla-La Mancha (Spain).Junta de Comunidades de Castilla-La Manch

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

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

Fractional Control of a Humanoid Robot Reduced Model with Model Disturbances

There is an open discussion between those who defend mass-distributed models for humanoid robots and those in favor of simple concentrated models. Even though each of them has its advantages and disadvantages, little research has been conducted analyzing the control performance due to the mismatch between the model and the real robot, and how the simplifications affect the controller's output. In this article we address this problem by combining a reduced model of the humanoid robot, which has an easier mathematical formulation and implementation, with a fractional order controller, which is robust to changes in the model parameters. This controller is a generalization of the well-known proportional-integral-derivative (PID) structure obtained from the application of Fractional Calculus for control, as will be discussed in this article. This control strategy guarantees the robustness of the system, minimizing the effects from the assumption that the robot has a simple mass distribution. The humanoid robot is modeled and identified as a triple inverted pendulum and, using a gain scheduling strategy, the performances of a classical PID controller and a fractional order PID controller are compared, tuning the controller parameters with a genetic algorithm.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-CM project (S2009/DPI-1559), funded by the Research and Development Work Programme of the Community of Madrid and cofunded by Structural Funds of the EU.Publicad

A New Approach of Soft Joint Based on a Cable-Driven Parallel Mechanism for robotic Applications

A soft joint has been designed and modeled to perform as a robotic joint with 2 Degrees of Freedom (DOF) (inclination and orientation). The joint actuation is based on a Cable-Driven Parallel Mechanism (CDPM). To study its performance in more detail, a test platform has been developed using components that can be manufactured in a 3D printer using a flexible polymer. The mathematical model of the kinematics of the soft joint is developed, which includes a blocking mechanism and the morphology workspace. The model is validated using Finite Element Analysis (FEA) (CAD software). Experimental tests are performed to validate the inverse kinematic model and to show the potential use of the prototype in robotic platforms such as manipulators and humanoid robots.The research leading to these results has received funding from the project Desarrollo de articulaciones blandas para aplicaciones robóticas, with reference IND2020/IND-1739, funded by the Comunidad Autónoma de Madrid (CAM) (Department of Education and Research), and from RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation Hub (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos, FaseIV; S2018/NMT-4331), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU

UAVs formation approach using fast marching square methods

This article presents a novel method for the management of UAVs formations. Based on the fast marching square (FM2) technique, the proposed method allows the generation of soft realizable paths for a formation in leader-followers configuration, keeping a desired geometry among its different agents. The solution presented here also allows the UAVs formation to adapt its shape so that the obstacles can be avoided, at the same time that a flight level can be fixed with respect to the ground. Simulation results will be presented in different environments to show the validity and robustness of the approach.This research was supported by 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

UAVs mission planning with flight level constraint using Fast Marching Square Method

In the last decade, Unmanned Aerial Vehicles (UAVs) have been a research focus for many purposes. Many of these studies require a path planning to perform autonomous flights, as well as the maintenance of a fixed flight level with respect to the ground to capture videos or overlying images. This article presents an approach to plan a mission for UAVs keeping a fixed flight level constraint. The 3D environment where the planning is carried out is an open field with non-uniform terrain. The approach proposed is based on the Fast Marching Square (FM ) method, which generates a path free from obstacles. Our approach includes two adjustment parameters. Depending on the values of these parameters, the restriction of flight level can be modified, as well as the smoothness and safety of the generated paths. Simulated experiments carried out in this work demonstrate that the proposed approach generates trajectories respecting a fixed flight level over the ground with successful results.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.Publicad

UAVs mission planning with imposition of flight level through fast marching square

Many proposed activities to be carried out by unmanned aerial vehicles (UAVs) in urban environments require a control over the altitude for different purposes. Energy saving and minimization of costs are some of these objectives. This work presents a method to impose a flight level in a mission planning carried out by a UAV in a 3D urban environment. The planning avoids all obstacles encountered in the environment and maintains a fixed flight level in the majority of the trajectory. The method used as planner is the Fast Marching Square (FM2) method, which includes two adjustment parameters. Depending on the values of these parameters, it is possible to introduce into the planning an altitude constraint, as well as to modify the smoothness of the trajectory and the safety margins from the obstacles. Several simulated experiments have been carried out in different situations obtaining very good results.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