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Aquest treball aborda el disseny i muntatge d’un prototip i la creació d’un sistema original capaç de mesurar la distància a una font sonora exclusivament a partir del senyal captat per un o més micròfons i tractant aquest senyal de manera adequada, amb l’objectiu de poder aplicar aquest sistema a la determinació de l’angle existent entre un robot mòbil i una persona que interaccioni amb ell amb unes distàncies predeterminades. El senyal de la font és d’una sola freqüència, també coneguda. El disseny del prototip consta d’una primera etapa analògica, que du a terme l’amplificació, el filtrat i la rectificació del senyal, i d’una segona etapa digital que s’encarrega de convertir la lectura del nivell de pressió sonora captat a voltatge mesurable. Paral·lelament al desenvolupament del prototip hi ha una important part de presa de mesures i d’estudi de les dades obtingudes d’un model teòric com pràctic per tal d’estudiar l’abast de la fórmula de conversió que s’utilitzarà. Finalment es comprovarà el funcionament del prototip dissenyat. Com a requisit per a poder desenvolupar el projecte es contempla la recerca d’informació i l’estudi de les diverses tecnologies i aparells, així com del marc teòric que l’engloba, és a dir, tot el referent a com es transmet el so i les diverses maneres de caracteritzar-lo Este trabajo aborda el diseño y montaje de un prototipo y la creación de un sistema original capaz de mesurar la distancia a una fuente sonora exclusivamente a partir de la señal captada por uno o más micrófonos y tratando esta señal de manera adecuada, con el objetivo de poder aplicar este sistema a la determinación del ángulo existente entre un robot móvil y una persona que interaccione con él con unas distancias predeterminadas. La señal de la fuente es de una sola frecuencia, también conocida. El diseño del prototipo consta de una primera etapa analógica, que lleva a cabo la amplificación, el filtrado y la rectificación de la señal, y de una segunda etapa digital que se encarga de convertir la lectura del nivel de presión sonora captado a voltaje medible. Paralelamente al desarrollo del prototipo, hay una importante parte de toma de medidas y de estudio de los datos obtenidos de un modelo tanto teórico como práctico para estudiar el alcance de la fórmula de conversión que se utilizará. Finalmente se comprobará el funcionamiento del prototipo diseñado. Como requisito para poder desarrollar el proyecto se contempla la investigación de información y el estudio de las varias tecnologías y aparatos, así como del marco teórico que lo engloba, es decir, todo lo en lo referente a cómo se transmite el sonido y las diversas maneras de caracterizarlo This work deals with the design and assembly of a prototype and the creation of an original system capable of measuring the distance to a sound source exclusively from the signal captured by one or more microphones and treating this signal adequately, with the aim of applying this system to the determination of the existing angle between a moving robot and a person interacting with it with predetermined distances. The source signal is a single frequency, also known. The prototype design consists of a first stage analogue, which performs amplified, filtered and corrected signal, and a second stage digital which converts the reading of the level of sound pressure captured to measurable voltage. In parallel to the development of the prototype, there is an important part of taking measures and studying the data obtained from a theoretical as practical model in order to study the scope of the conversion formula to be used. Finally, the operation of the designed prototype will be checked. Research into information and the study of the various technologies and devices and the theoretical framework that includes it are a prerequisite for the development of the project, everything relating to how sound is transmitted and the various ways of characterizing it

One of the main goals in robotics is to achieve full autonomy. However, for certain tasks, robots still lack the level of abstract reasoning that gives the ability to make decisions, plan ahead, and change actions during the execution of a process, these abilities are acquired at its best degree only by humans. In terms of unknown underwater environments, the combination of specialized robotics that can withstand harsh environments and the reasoning of a human operator can give effective results on exploration, inspection, and subsequent tasks. Standard solutions propose to use fully teleoperated Remotely Operated Vehicles (ROV)s or fully Autonomous Underwater Vehicles (AUV). Still, both solutions have their drawbacks: high operation costs and limitations due to the need of a physical connection in the case of ROVs, and limitations in the communications or problems while facing complex decision making in case of AUVs. These limitations can be overcome with the concept of shared autonomy applied to a Hybrid ROV (HROV). In this new paradigm, an operator leads the mission by selecting objectives at a high level, and a HROV executes them taking all the low level decisions. This paper explores the shared autonomy concept applied to an underwater exploration task, leading the first steps towards intervention missions.

L’ús de sistemes autònoms amb bateries recarregables és cada cop més estès a la indústria, especialment en aplicacions robòtiques. Les noves plataformes robòtiques requereixen una alta autonomia per poder allargar la durada dels processos, a més de la capacitat de predir quan s’esgotarà l’energia per a carregar el sistema, avortar tasques, o tornar a una estació base. Per aquest motiu, la correcta estimació del State-of-Charge (SoC) per poder monitorar l’estat de la bateria i garantir un correcte funcionament del dispositiu és una aplicació altament demandada. En aquest treball es proposa desenvolupar, implementar i testejar un sistema que estimi el SoC d’una bateria i enviar-lo a un ordinador central perquè, en cada cas, prengui la decisió oportuna. El resultat final es provarà en una plataforma autònoma real de l’empresa PAL Robotics. El projecte desenvoluparà la programació de l’algoritme per monitorar el nivell de càrrega de les bateries. Aquestes dades seran transmeses a l’ordinador central mitjançant el protocol Universal Serial Bus (USB), juntament amb altres dades del robot. D’aquesta manera, en aquest document s’explica detalladament com s’han desenvolupat les tasques que permeten caracteritzar i validar els drivers per PAL Robotics. Als annexes s’inclouen els header files de la solució proposada així com també els scripts i experiments que han permès desenvolupar i/o comprovar el funcionament d’aquests. Després d’haver realitzat aquestes tasques, s’ha pogut comprovar que la feina implementada en aquest TFG és vàlida donat que es superen els requeriments tècnics demanats per l’empresa. El uso de sistemas autónomos con baterías recargables es cada vez más extendido en la industria, especialmente en aplicaciones robóticas. Las nuevas plataformas robóticas requieren una alta autonomía para poder alargar la duración de los procesos, además de la capacidad de predecir cuándo se agotará la energía para cargar el sistema, abortar tareas, o volver a una estación base. Por este motivo, la correcta estimación del State-of-Charge (SoC) para poder monitorizar el estado de la batería y garantizar un correcto funcionamiento del dispositivo es una aplicación altamente demandada. En este trabajo se propone desarrollar, implementar y testear un sistema que estime el SoC de una batería y enviarlo a un ordenador central para que, en cada caso, tome la decisión oportuna. El resultado final se probará en una plataforma autónoma real de la empresa PAL Robotics. El proyecto desarrollará la programación del algoritmo para monitorizar el nivel de carga de las baterías. Estos datos serán transmitidos al ordenador central mediante el protocolo Universal Serial Bus (USB), junto con otros datos del robot. De este modo, en este documento se explica detalladamente cómo se han desarrollado las tareas que permiten caracterizar y validar los drivers por PAL Robotics. En los anexos se incluyen los header files de la solución propuesta, así como los scripts y experimentos que han permitido desarrollar y/o comprobar el funcionamiento de los mismos. Después de haber realizado estas tareas, se ha podido comprobar que el trabajo implementado en este TFG es válido dado que se superan los requerimientos técnicos solicitados por la empresa. The use of autonomous systems with rechargeable batteries is becoming more widespread in the industry, especially in robotic applications. New robotic platforms require high autonomy to be able to extend the duration of processes, as well as the ability to predict when the power will run out to charge the system, abort tasks, or return to a base station. For this reason, the correct estimation of the State-of-Charge (SoC) to be capable to monitor the battery status and guarantee the correct operation of the device is a highly demanded application. In this work, we propose to develop, implement and test a system that estimates the SoC of a battery and sends it to a central computer to make the appropriate decision in each case. The proposal will be tested on a real autonomous platform of the company PAL Robotics. The project will develop the programming of the algorithm to monitor the charge level of the batteries. This data will be transmitted to the host computer via Universal Serial Bus (USB) protocol and other robot data. In this way, this document explains in detail how the tasks that allow the drivers to be characterized and validated by PAL Robotics have been developed. The annexes include the header files of the proposed solution, as well as the scripts and experiments that have allowed to develop and/or test the operation of the same. After having carried out all these experiments, it has been possible to verify that the work implemented in this TFG is valid since the technical requirements requested by the company are exceeded.

Underwater 3D laser scanners are an essential type of sensor used by unmanned underwater vehicles (UUVs) for operations such as navigation, inspection and object recognition and manipulation. These sensors need to be able to provide highly accurate 3D data at fast refresh rates in order to accomplish these tasks. Usually, these scanners rely on a rotating mirror actuated by a galvanometer. However, the light planes steered by this type of mirrors are typically deformed into cones due to refraction. In order to produce accurate results, this distortion needs to be taken into account, which increases the computational cost of the 3D reconstruction. A novel approach consisting in using a biaxial MEMS mirror is proposed in this paper. The second rotational degree of freedom of the mirror can be used to project optimally curved light shapes, so that the refraction process transforms them into planes. Being able to model the light surfaces as planes rather than cones can significantly reduce the computation time of the 3D reconstruction. In order to do so, an exhaustive model of the complete light trajectories is presented. To the best of the authors' knowledge, this paper constitutes the first attempt to model and counteract the distortion in the scanning pattern introduced by a biaxial mirror and a double refraction process in the context of underwater robotics This work was supported in part by the Spanish Ministry of Science through the GIRONA1000 Project under Grant DPI2017-86372-C3-2-R, in part by the European Commission through the ATLANTIS Project under Grant H2020-ICT-2019-2-871571, and in part by the Doctoral Grant of the University of Girona under Grant IFUdG2019

Treballs recents sobre localització de vehicles i mapeig dels seus entorns es desenvolupen per a dispositius portàtils o robots terrestres que assumeixen moviments lents i suaus. Contràriament als entorns de curses d’alta velocitat. Aquesta tesi proposa un nou model d’SLAM, anomenat LIMO-Velo, capaç de corregir el seu estat amb una latència extremadament baixa tractant els punts LiDAR com un flux de dades. Els experiments mostren un salt en robustesa i en la qualitat del mapa mantenint el requisit de correr en temps real. El model aconsegueix una millora relativa del 20% en el KITTI dataset d’odometria respecte al millor rendiment existent; no deriva en un sol esce- nari. La qualitat del mapa a nivell de centı́metre es manté amb velocitats que poden arribar a 20 m/s i 500 graus/s. Utilitzant les biblioteques obertes IKFoM i ikd-Tree, el model funciona x10 més ràpid que la majoria de models d’última generació. Mostrem que LIMO-Velo es pot generalitzar per exe- cutar l’eliminació dinàmica d’objectes, com ara altres agents a la carretera, vianants i altres. Trabajos recientes sobre la localización de vehı́culos y el mapeo de sus en- tornos se desarrollan para dispositivos portátiles o robots terrestres que asumen movimientos lentos y suaves. Al contrario de los entornos de carreras de alta velocidad. Esta tesis propone un nuevo modelo SLAM, LIMO-Velo, capaz de corregir su estado en latencia extremadamente baja al tratar los puntos LiDAR como un flujo de datos. Los experimentos muestran un salto en la solidez y la calidad del mapa mientras se mantiene el requisito de tiempo real. El modelo logra una mejora relativa del 20% en el conjunto de datos de KITTI Odometry sobre el mejor desempeño existente; no deriva en un solo escenario. La calidad del mapa de nivel centimétrico todavı́a se logra a velocidades de carrera que pueden llegar hasta 20 m/s y 500 grados/s. Us- ando las bibliotecas abiertas IKFoM e ikd-Tree, el modelo funciona x10 más rápido que la mayorı́a de los modelos de última generación. Mostramos que LIMO-Velo se puede generalizar para trabajar bajo la eliminación dinámica de objetos, como otros agentes en la carretera, peatones y más. Recent works on localizing vehicles and mapping their environments are de- veloped for handheld devices or terrestrial robots which assume slow and smooth movements. Contrary to high-velocity racing environments. This thesis proposes a new SLAM model, LIMO-Velo, capable of correcting its state at extreme low-latency by treating LiDAR points as a data stream. Experiments show a jump in robustness and map quality while maintaining the real-time requirement. The model achieves a 20% relative improvement on the KITTI Odometry dataset over the existing best performer; it does not drift in a single scenario. Centimeter-level map quality is still achieved under racing velocities that can go up to 20m/s and 500deg/s. Using the IKFoM and ikd-Tree open libraries, the model performs x10 faster than most state-of-the-art models. We show that LIMO-Velo can be generalized to work under dynamic object removal such as other agents in the road, pedestrians, and more. Outgoing

Robots are usually equipped with 3D range sensors such as laser line scanners (LLSs) or lidars. These sensors acquire a full 3D scan in a line by line manner while the robot is in motion. All the lines can be referred to a common coordinate frame using data from inertial sensors. However, errors from noisy inertial measurements and inaccuracies in the extrinsic parameters between the scanner and the robot frame are also projected onto the shared frame. This causes a deformation in the final scan containing all the lines, which is known as motion distortion. Rigid point cloud registration with methods like ICP is therefore not well suited for such distorted scans. In this paper we present a non-rigid registration method that finds the rigid transformation to be applied to each line in the scan in order to match an existing model. We fully leverage the continuous and relatively smooth robot motion with respect to the scanning time to formulate our method reducing the computational complexity while improving accuracy. We use synthetic and real data to benchmark our method against a state-of-the-art non-rigid registration method. Finally, the source code for the algorithm is made publicly available., IEEE Robotics and Automation Letters, 7 (3), ISSN:2377-3766

This article studies the design, modeling, and implementation of a path-following algorithm as a guidance, navigation, and control (GNC) architecture for an autonomous underwater vehicle (AUV). First, a mathematical model is developed based on nonlinear equations of motion and parameter estimation techniques, including the model validation based on field test data. Then, the guidance system incorporates a line-of-sight (LOS) algorithm with a combination of position PID controllers. The GNC architecture includes a modular and multi-layer approach with an LOS-based, path-following algorithm in the AUV platform. Furthermore, the navigation used in the path-following algorithm is developed based on a predefined coverage area. Finally, this study addresses simulation and field test control scenarios to verify the developed GNC architecture This research was funded by the project MOCAV-G500 from EUMarineRobots that has received funding from the European Union’s Horizon 2020 (grant agreement No 731103), with the collaboration of the aColor project, which is funded by Technology Industries of Finland Centennial and Jane & Aatos Erkko Foundations

Aquest document presenta un mil·lirobot autònom que persegueix un camp magnètic. El robot és senzill i petit de 57 mm per 49 mm per 18,5 mm i és capaç de rastrejar el camp magnètic. Es presenta i s’explica com s’ha dissenyat i fabricat el robot, el seu control, el seu model dinàmic com l’agorisme elaborat i la presa de decisions autònomes. El robot té moltes aplicacions possibles, com ara el seguiment d’SPIONS al cervell en el pacients que tenen càncer cerebral This document presents an autonomous swimming millirobot driven by a magnetic field. The boat is simple and small (57mm by 49mm by 18.5mm) and it can track the magnetic field. The development of the hardware and algorithm is presented as its dynamic model, perception, and autonomous decision making. The robot has many possible applications, such as tracking SPIONS in the brain Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura

This paper presents the development of unmanned marine robotic control modelling and control synthesis using a coupled multivariable underactuated nonlinear adaptive U-model approach. The proposed controller was developed using thru an open source robot operating system (ROS) platform. The new adaptive coupled U-model based internal model control (IMC) node was successfully developed and tested. The proposed controller demonstrated the simplicity of the control synthesis process and the implementation of the mathematical algorithm in real-time. The controller was compared with the proven existing GIRONA 500 UUV for real-time performance. The ROS environment provides fast and reliable controller design and development compared to conventional software architecture. Simulation and real-time experiment were conducted using ROS via the GIRONA 500 UUV platform and compared with a PID mission controller. A new ROS node of nonlinear adaptive U-model based IMC was developed using ROS. The results showed good control signal convergence and tracking performance between the plant or system model with the proposed method This research was supported by the Yayasan Universiti Teknologi Petronas-Fundamental Research Grant-Petroleum Resource Fund (YUTP-FRG) funded by PRF under the grant 0015LC0-235, Universiti Teknologi PETRONAS, Malaysia and King Abdulaziz University, Jeddah, Saudi Arabia under the grant 015ME0-066

With the arrival of Industry 4.0, traditional manufactures will undergo a digitalization and automatization process to become smart factories. In such warehouses, fleets of fully autonomous robots will cooperate to transport required items from one place to another. In this context, it is important to guarantee that robots follow optimal collision-free trajectories. For this project, a setting with two KMR iiwa robots in a warehouse crossing is considered. These robots are composed of two main parts: the LBR iiwa (a mechanical arm) and the KMP iiwa (a holonomic mobile platform). Algorithms to control the KMP iiwa have been designed and implemented in ROS, and then tested using the simulator Gazebo. Starting from an already existing ROS-Gazebo model of the KMR iiwa, a closed-loop control system for navigation has been set up. Then, a navigation algorithm (to drive a single KMR iiwa robot by giving it a set of way-points) has been implemented. Afterwards, a collision avoidance strategy was added to the navigation algorithm. The designed policy took into account noisy data from laser scanners incorporated in the robot. To test the proposed strategy, several experiments have been performed considering various scenarios. The outcomes of these tests are analysed in this report. Finally, some conclusions and possible future work are presented. Con la llegada de la Industria 4.0, las fábricas tradicionales se verán sometidas a un proceso de digitalización i automatización para convertir-se en fábricas inteligentes. En estas manufacturas, flotas de robots autónomos colaboraran para transportar artículos necesarios de un punto a otro. En este contexto, es importante garantizar que los robots seguirán trayectorias óptimas, sin sufrir colisiones. En este proyecto, se ha considerado la situación de dos robots KMR iiwa navegando en una fábrica, dirigiéndose al mismo cruce de pasillos. Este tipo de robots está formado por: un LBR iiwa (un brazo mecánico) i un KMP iiwa (una plataforma holonòmica). En este trabajo, se han diseñado e implementado algoritmos de control para la KMP iiwa, utilizando ROS. El código desarrollado ha sido testado con el simulador Gazebo. Partiendo de un modelo ROS-Gazebo ya existente del robot KMR iiwa, un sistema de control en lazo cerrado ha sido implementado. Después, se ha desarrollado un algoritmo de navegación, con el que se puede conducir el robot KMR iiwa pasándole varios puntos de referencia del entorno. A continuación, se ha añadido una estrategia para evitar colisiones entre robots al algoritmo de navegación. El método diseñado tiene en consideración la información (con ruido) procedente de los escáneres laser con que el robot está equipado. Para testear la estrategia propuesta, se han llevado a cabo varios experimentos en distintos escenarios. El resultado de estos experimentos es analizado en este documento. Finalmente, se exponen las conclusiones del trabajo i posibles mejoras. Amb l'arribada de la Indústria 4.0, les fàbriques tradicionals es veuran sotmeses a un procés de digitalització i automatització per esdevenir fàbriques intel·ligents. En aquestes manufactures, flotes de robots autònoms cooperaran per transportar articles necessaris d'un lloc a un altre. En aquest context, és important garantir que els robots seguiran trajectòries òptimes, sense patir cap col·lisió. En aquest projecte, s'ha considerat la situació de dos robots KMR iiwa navegant en una fàbrica, dirigint-se al mateix encreuament de passadissos. Aquest tipus de robots estan formats per dues parts: un LBR iiwa (un braç mecànic) i un KMP iiwa (una plataforma holonòmica). En aquest treball, s'han dissenyat i implementat algoritmes de control per la KMP iiwa, fent servir ROS. El codi desenvolupat ha estat testat amb el simulador Gazebo. Partint d'un model ROS-Gazebo ja existent del robot KMR iiwa, un sistema de control en llaç tancat ha estat implementat. Després, s'ha desenvolupat un algoritme de navegació, amb el que es pot conduir el robot KMR iiwa passant-li un seguit de punts de referència del entorn. A continuació, s'ha afegit una estratègia per evitar col·lisions entre robots al algoritme de navegació. El mètode dissenyat té en compte la informació (amb soroll) proveint dels escàners làser amb els que estava equipat el robot. Per testar la estratègia proposada, s'han dut a terme varis experiments en diferents escenaris. El resultat d'aquests experiments son presentats en aquest document. Finalment, s'exposen les conclusions del treball i possibles millores.

In this paper, we compare liability rules in a world where human-driven and fully-autonomous cars coexist. We develop a model where a manufacturer can invest to improve the safety of autonomous cars. Human drivers may decide to purchase a fully-autonomous car to save precaution costs to avoid road accidents and shift liability to the car manufacturer. As compared to the negligence rule, a strict liability regime on both human drivers and car manufacturers is proved to be a superior policy. In particular, strict liability leads to more efficient R&D investments to enhance the benefits of the technology and favors the adoption of fully-autonomous cars. We also recommend that users of fully-autonomous cars make a technology-dependent payment to a third-party if there is an accident to discipline their activity levels.

With the arrival of Industry 4.0, traditional manufactures will undergo a digitalization and automatization process to become smart factories. In such warehouses, fleets of fully autonomous robots will cooperate to transport required items from one place to another. In this context, it is important to guarantee that robots follow optimal collision-free trajectories. For this project, a setting with two KMR iiwa robots in a warehouse crossing is considered. These robots are composed of two main parts: the LBR iiwa (a mechanical arm) and the KMP iiwa (a holonomic mobile platform). Algorithms to control the KMP iiwa have been designed and implemented in ROS, and then tested using the simulator Gazebo. Starting from an already existing ROS-Gazebo model of the KMR iiwa, a closed-loop control system for navigation has been set up. Then, a navigation algorithm (to drive a single KMR iiwa robot by giving it a set of way-points) has been implemented. Afterwards, a collision avoidance strategy was added to the navigation algorithm. The designed policy took into account noisy data from laser scanners incorporated in the robot. To test the proposed strategy, several experiments have been performed considering various scenarios. The outcomes of these tests are analysed in this report. Finally, some conclusions and possible future work are presented. Con la llegada de la Industria 4.0, las fábricas tradicionales se verán sometidas a un proceso de digitalización i automatización para convertir-se en fábricas inteligentes. En estas manufacturas, flotas de robots autónomos colaboraran para transportar artículos necesarios de un punto a otro. En este contexto, es importante garantizar que los robots seguirán trayectorias óptimas, sin sufrir colisiones. En este proyecto, se ha considerado la situación de dos robots KMR iiwa navegando en una fábrica, dirigiéndose al mismo cruce de pasillos. Este tipo de robots está formado por: un LBR iiwa (un brazo mecánico) i un KMP iiwa (una plataforma holonòmica). En este trabajo, se han diseñado e implementado algoritmos de control para la KMP iiwa, utilizando ROS. El código desarrollado ha sido testado con el simulador Gazebo. Partiendo de un modelo ROS-Gazebo ya existente del robot KMR iiwa, un sistema de control en lazo cerrado ha sido implementado. Después, se ha desarrollado un algoritmo de navegación, con el que se puede conducir el robot KMR iiwa pasándole varios puntos de referencia del entorno. A continuación, se ha añadido una estrategia para evitar colisiones entre robots al algoritmo de navegación. El método diseñado tiene en consideración la información (con ruido) procedente de los escáneres laser con que el robot está equipado. Para testear la estrategia propuesta, se han llevado a cabo varios experimentos en distintos escenarios. El resultado de estos experimentos es analizado en este documento. Finalmente, se exponen las conclusiones del trabajo i posibles mejoras. Amb l'arribada de la Indústria 4.0, les fàbriques tradicionals es veuran sotmeses a un procés de digitalització i automatització per esdevenir fàbriques intel·ligents. En aquestes manufactures, flotes de robots autònoms cooperaran per transportar articles necessaris d'un lloc a un altre. En aquest context, és important garantir que els robots seguiran trajectòries òptimes, sense patir cap col·lisió. En aquest projecte, s'ha considerat la situació de dos robots KMR iiwa navegant en una fàbrica, dirigint-se al mateix encreuament de passadissos. Aquest tipus de robots estan formats per dues parts: un LBR iiwa (un braç mecànic) i un KMP iiwa (una plataforma holonòmica). En aquest treball, s'han dissenyat i implementat algoritmes de control per la KMP iiwa, fent servir ROS. El codi desenvolupat ha estat testat amb el simulador Gazebo. Partint d'un model ROS-Gazebo ja existent del robot KMR iiwa, un sistema de control en llaç tancat ha estat implementat. Després, s'ha desenvolupat un algoritme de navegació, amb el que es pot conduir el robot KMR iiwa passant-li un seguit de punts de referència del entorn. A continuació, s'ha afegit una estratègia per evitar col·lisions entre robots al algoritme de navegació. El mètode dissenyat té en compte la informació (amb soroll) proveint dels escàners làser amb els que estava equipat el robot. Per testar la estratègia proposada, s'han dut a terme varis experiments en diferents escenaris. El resultat d'aquests experiments son presentats en aquest document. Finalment, s'exposen les conclusions del treball i possibles millores.

In this field note, we detail the operations and discuss the results of an experiment conducted in the unstructured environment of an underwater cave complex using an autonomous underwater vehicle (AUV). For this experiment, the AUV was equipped with two acoustic sonar sensors to simultaneously map the caves' horizontal and vertical surfaces. Although the caves' spatial complexity required AUV guidance by a diver, this field deployment successfully demonstrates a scan‐matching algorithm in a simultaneous localization and mapping framework that significantly reduces and bounds the localization error for fully autonomous navigation. These methods are generalizable for AUV exploration in confined underwater environments where surfacing or predeployment of localization equipment is not feasible, and they may provide a useful step toward AUV utilization as a response tool in confined underwater disaster areas This research work was partially sponsored by the EU FP7-Projects: Tecniospring- Marie Curie (TECSPR13-1-0052), MORPH (FP7-ICT-2011-7-288704), Eurofleets2 (FP7-INF-2012-312762), and the National Science Foundation (OCE-0955674).

Nowadays, autonomous robots for all different purposes are the state-of-the-art technology, all companies across the industry are implementing all kind of autonomous machines to control and computerize the industrial systems and processes, making errors virtually impossible and, despite all the first investment, the transition pays off in the mid and long-term because of all the time and resources saved. This new industrial phase, which is a current tendency commonly known as Industry 4.01 , focuses on interconnectivity, automation, machine learning, and real-time data. The same trend applies to vehicles or mobile machines (for industrial or non-industrial purposes), the use of fossil fuels is decreasing whereas the implementation of automation and systems of artificial intelligence is strongly increasing day by day. Heavy-duty hydraulically driven mobile working machines (for mining, construction, forestry, and material handling purposes) are also in constant development for increasing efficiency and performance because of the higher requirements set by the constant growth of this sector. As a result, working machines are increasingly expected to become more precise, and robotics like towards autonomous operation. This thesis studies the design requirements and sizing for each hydraulic actuator system of the case of study, a long-reach manipulator 4x4 Haulotte HA16 RTJ PRO which is available at the University of Tampere (Hervanta Campus). This hydraulic articulated boom, originally manually driven, is being redesigned into a servo-hydraulic system maintaining the original diesel motor source and taking into account its limited power. The general work consists of requirements of development, hydraulic engineering designs, component selection, modeling, and simulations towards a new prototyped system meeting the set requirements. During the making of this thesis, the component selection was already done and the scope of the study relies on the kinematic and hydraulic analysis for the vehicle. Also, this thesis has pursued another objective, which is the compilation of technical data (such as the boom dimensions, original hydraulics, or technical information about the main components) among the different reports about the Haulotte, trying to achieve that the upcoming students or researchers can get clearer ideas and the maximum possible information about the case of study reading this document. The goals are got from a theoretical viewpoint through equations and hypotheses considered throughout the study, therefore, the results obtained must be taken as approximations. The reason is the coronavirus pandemic, which forced the university and the laboratories to close since the beginning of the semester and some parameters or variables taken may not always coincide with the reality because were taken from a 3D model from the original Haulotte website. Keywords: Wheeled Mobile Robot, Mobile platform, Hydraulics, Automation, Kinematics, Haulotte, HA16 RTJ PRO, Boom, Articulating boom lift, 4WSD

L’empresa de robòtica mòbil MiR està introduïnt al mercat els robots AMR (Autonomous Mobile Robots), els quals es caracteritzen pel fet de no ser guiats. És a dir, aquesta tipologia de robot no necessita de cap ajuda externa per al seu moviment, fet pel qual és necessaria una bona detecció dels objectes estàtics i dinàmics per evitar colisions. Des de MiR es vol desenvolupar un dispositiu que permeti el control de tràfic de les fàbriques a partir d’una comunicació remota. L’objectiu del disseny d’aquest dispositiu és poder saber la posició d’un objecte dins la fàbrica i comunicar-se amb els robots. En funció de l’existència d’algun impediment, aquests podran passar, o no, per determinats llocs, entre altres. El present projecte consisteix en la programació d’un dispositiu basat en una Raspberry Pi per al càlcul del seu posicionament en interiors i la comunicació de forma remota amb la flota de robots MiR; el sistema de gestió de robots pròpi de MiR. Per aquest motiu, en el codi desenvolupat s’hi troba el càlcul del posicionament en interiors a partir de la tirangulació de WIFI i els codis per a la comunicació remota per a obtenir els mapes dels robots i les zones d’aquests. També s’hi troba la verificació de si l’objecte que té el dispositiu es troba dins d’una zona de límit de robots, i en el cas que s’hi trobi, es bloquegi la zona per tal que cap robot pugui entrar-hi. D’aquesta manera, s’evita que el robot arribi a mostrar un error per no poder passar per un determinat lloc, i també s’eviten possibles col·lisions. La empresa de robótica móbil MiR está introduciendo en el mercado los robots AMR (Autonomous Mobile Robots), los cuales se caracterizan por el hecho de no ser guiados. Es decir, esta tipología de robots no necesita de ninguna ayuda externa para su movimiento, por lo que es necesaría una buena deteccón de los objetos estáticos y dinámicos para evitar colisiones. Des de MiR se quiere desarrollar un dispositivo que permita el control del tráfico de la fábricas a partir de una comunicación remota. El objetivo del diseño de este dispositivo es poder saber la posición de un objeto dentro de la fábrica y comunicar-se con los robots. En función de la existencia de algun impedimiento, éstos podran pasar, o no, por determinados sitios, entre otras cosas. El presente proyecto consiste en la programación de un dispositivo basado en una Raspberry Pi para el cálculo de su posicionamiento en interiores y la comunicación de forma remota con una flota de robots MiR; el sistema de gestión de robots propio de MiR. Por este motivo, en el código desarrollado se encuentra el cálculo del posicionamiento en interiores a partir de la triangulación de WIFI y los códigos para la comunicación remota para obtener los mapas de los robots y las zonas de estos. También se encuentra la verificación de si un objeto que posee el dispositivo se encuentra dentro de una zona de límite de robots, y en el caso que se encuentre, se bloquee la zona para que ningún robot pueda entrar. De esta forma, se evita que el robot llegue a enseñar un error por no poder pasar por un determinado sitio, y también se evitan posibles colisiones. The mobile robotics company MiR is introducing the AMR (Autonomous Mobile Robots) robots in the market, which are characterized by not being guided. This means, that this type of robot needs not any external help to move, this is why a good dynamic and static objects detection is necessary to avoid collisions. From MiR, we want to develop a device that allows the control of factory traffic using remote communication. The objective of the device design is to be able to know an object position in a factory and communicate with robots. Depending on the existence of some impediment, these may or may not pass through certain sites, among other things. The current project consists of the programming of a device based on a Raspberry Pi for the calculation of its indoor positioning and remote communication with a MiR robots Fleet; MiR’s own robot management system. For this reason, the code developed includes the calculation of the indoor positioning from the WIFI triangulation and the codes for the remote communication to get the robot maps and their zones. There is also the verification of whether an object held by the device is in a limit robots zone, and if it is, the zone is blocked so that no robot can enter. In this way, the robot is prevented from showing an error because it cannot pass through a certain place, and possible collisions are also avoided.

One of the problems that service robotics deals with is to bring mobile manipulators to work in semi-structured human scenarios, which requires an efficient and flexible way to execute every-day tasks, like serve a cup in a cluttered environment. Usually, for those tasks, the combination of symbolic and geometric levels of planning is necessary, as well as the integration of perception models with knowledge to guide both planning levels, resulting in a sequence of actions or skills which, according to the current knowledge of the world, may be executed. This paper proposes a planning and execution framework, called SkillMaN, for robotic manipulation tasks, which is equipped with a module with experiential knowledge (learned from its experience or given by the user) on how to execute a set of skills, like pick-up, put-down or open a drawer, using workflows as well as robot trajectories. The framework also contains an execution assistant with geometric tools and reasoning capabilities to manage how to actually execute the sequence of motions to perform a manipulation task (which are forwarded to the executor module), as well as the capacity to store the relevant information to the experiential knowledge for further usage, and the capacity to interpret the actual perceived situation (in case the preconditions of an action do not hold) and to feed back the updated state to the planner to resume from there, allowing the robot to adapt to non-expected situations. To evaluate the viability of the proposed framework, an experiment has been proposed involving different skills performed with various types of objects in different scene contexts

Encoding practical knowledge about everyday activities has proven difficult, and is a limiting factor in the progress of autonomous robotics. Learning approaches, e.g. imitation learning from human data, have been used as a way to circumvent this difficulty. While such approaches are on the right track, they require comprehensive knowledge modelling about the data present in records of activity episodes, and about the skills one attempts to have the robot learn. We provide a list of competency questions such knowledge modelling should answer, summarize some recent developments in this direction, and finish with a few open problems.

Autonomous indoor service robots are supposed to accomplish tasks, like serve a cup, which involve manipulation actions. Particularly, for complex manipulation tasks which are subject to geometric constraints, spatial information and a rich semantic knowledge about objects, types, and functionality are required, together with the way in which these objects can be manipulated. In this line, this paper presents an ontological-based reasoning framework called Perception and Manipulation Knowledge (PMK) that includes: (1) the modeling of the environment in a standardized way to provide common vocabularies for information exchange in human-robot or robot-robot collaboration, (2) a sensory module to perceive the objects in the environment and assert the ontological knowledge, (3) an evaluation-based analysis of the situation of the objects in the environment, in order to enhance the planning of manipulation tasks. The paper describes the concepts and the implementation of PMK, and presents an example demonstrating the range of information the framework can provide for autonomous robots.

We present an approach to endow an autonomous underwater vehicle with the capabilities to move through unexplored environments. To do so, we propose a computational framework for planning feasible and safe paths. The framework allows the vehicle to incrementally build a map of the surroundings, while simultaneously (re)planning a feasible path to a specified goal. To accomplish this, the framework considers motion constraints to plan feasible 3D paths, that is, those that meet the vehicle’s motion capabilities. It also incorporates a risk function to avoid navigating close to nearby obstacles. Furthermore, the framework makes use of two strategies to ensure meeting online computation limitations. The first one is to reuse the last best known solution to eliminate time-consuming pruning routines. The second one is to opportunistically check the states’ risk of collision. To evaluate the proposed approach, we use the Sparus II performing autonomous missions in different real-world scenarios. These experiments consist of simulated and in-water trials for different tasks. The conducted tasks include the exploration of challenging scenarios such as artificial marine structures, natural marine structures, and confined natural environments. All these applications allow us to extensively prove the efficacy of the presented approach, not only for constant-depth missions (2D), but, more important, for situations in which the vehicle must vary its depth (3D) J.D. Hern´andez, E. Vidal, N. Palomeras, and M. Carreras have been supported by the EXCELLABUST and ARCHROV Projects under the Grant agreements H2020-283TWINN-2015, CSA, ID: 691980 and DPI2014- 57746-C3-3-R respectively

The goal of the TFG would be to implement an object recognition system for an autonomous robot within the GRASS (Ground Autonomous Student Station) project. The idea is to use two cameras and be able to juxtapose the images and create a 3D vision of what the system is seeing (in our case the rover), and be able to differentiate different predetermined objects by the shape, and if it's possible by the color. The purpose consists in recognizing the position and the orientation of these objects with respect to the rover as the considered reference system. The GRound Autonomous Student Station (GRASS) is a student organization with the objective of building an autonomous rover, and one of the capacities needed is the possibility of identifying objects. This project is focused on creating a recognition system capable of being incorporated on the Rover. The developed recognition system is focused on detection by colour and shape, using four colours and one predetermined cylindrical shape. The system has to identify the distance between the object and the camera. The developed system includes a Raspberry Pi system with his camera, using Python and OpenCV libraries as software. The developed system has been tried in a real model, but the final implementation has not been ended due to reasons related with the GRASS project. The structural and logistic parts of the project are developing a new space distribution in order to include eciently the recognition system, although the system has been tested. The developed system is capable of detecting determined objects with a simple shape in a maximum range of 12 meters. At the same time, it works on real environments, counting illumination and environmental visual noise.

This paper describes a pose-based underwater 3D Simultaneous Localization and Mapping (SLAM) using a multibeam echosounder to produce high consistency underwater maps. The proposed algorithm compounds swath profiles of the seafloor with dead reckoning localization to build surface patches (i.e., point clouds). An Iterative Closest Point (ICP) with a probabilistic implementation is then used to register the point clouds, taking into account their uncertainties. The registration process is divided in two steps: (1) point-to-point association for coarse registration and (2) point-to-plane association for fine registration. The point clouds of the surfaces to be registered are sub-sampled in order to decrease both the computation time and also the potential of falling into local minima during the registration. In addition, a heuristic is used to decrease the complexity of the association step of the ICP from O(n2) to O(n). The performance of the SLAM framework is tested using two real world datasets: First, a 2.5D bathymetric dataset obtained with the usual down-looking multibeam sonar configuration, and second, a full 3D underwater dataset acquired with a multibeam sonar mounted on a pan and tilt unit This work was supported by the Spanish project DPI2014-57746-C3-3-R (ARCHROV) and two European Commission’s Seventh Framework Program projects: FP7-ICT-2011-7-288704 (MORPH) and FP7-INFRASTRUCTURES-2012-312762 (EUROFLEETS2)

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm.

Research article compendium : peace and conflict research The University of Barcelona, in collaboration with different Spanish and foreign institutions and universities, hosted an international workshop on the ‘Sense and Scope of Autonomy in Emerging Military and Security Technologies’, which took place in February 2017. This academic event paved the way to the elaboration of the present report, which contains a compendium of innovative articles written by experts on scientific, legal, diplomatic and military matters. All papers reflect a broad spectrum of views on how ‘autonomy’ can be understood in emerging military and security technologies and what their legal, technical, political and societal impacts are by building on discussions unfolded along a variety of reflective approaches.

It is at least two decades since the conventional robotic manipulators have become a common manufacturing tool for different industries, from automotive to pharmaceutical. The advances in manipulators and sensors have given robots the opportunity to become useful for more and more applications. Engineers have taken advantage of the extra mobility of the advanced robots to make them work in constrained environments, ranging from limited joint motions for redundant manipulators to obstacles in the way of mobile (ground, marine, and aerial) robots [1]. However, the incorporation some of these abilities and capacities that are already being used in land, have not made their way to the sea domain. This Abstract describes the project consisting in the design, development and manufacture of a prototype manipulator arm for ROVs introducing innovative fabrication technologies. The work has been done collaboratively among ACSM Maritime Agency SL, CIMA Group and the University of Vigo.

Treball desenvolupat dins el marc del programa 'European Project Semester'. The robotics facilities at Oslo and Akershus University College of Applied Sciences (HiOA) have at their disposal an autonomous humanoid robot by the name of Nao. It is a commercial product developed by SoftBank Robotics for research and educational purposes, and an international project team was assembled for the European Project Semester (EPS) program as a means of assessing its competencies and bolstering them wherever possible. The team set forth with a mission to establish meaningful interactions between the robot and his physical surroundings while placing an emphasis on humanlike behavior to the fullest extent. A goal was soon initiated for Nao to play a rule-based game against a human opponent such that his vast array of available faculties could be tested and put to use in one cohesive demonstration. Achieving this goal meant making advances in artificial intelligence,computer vision and motion planning, first as separate entities that would later converge into a singular yet multifaceted display of abilities. At the end of the project, computer vision has been implemented to the point where pattern recognition can be performed with accuracy amidst awide variety of error-prone detection scenarios. Several artificial intelligence schemes have been explored and compared quantitatively to derive performance metrics for each. Proof-ofconcept movement strategies have also been derived, and best practices for each focus area are provided as a resource for any future researchers or project groups who stand to benefit from the discoveries made in this endeavor

This work introduces new results on the modeling of early-vocal development using artificial intelligent cognitive architectures and a simulated vocal tract. The problem is addressed using intrinsically-motivated learning algorithms for autonomous sensorimotor exploration, a kind of algorithm belonging to the active learning architectures family. The artificial agent is able to autonomously select goals to explore its own sensorimotor system in regions where its competence to execute intended goals is improved. We propose to include a somatosensory system to provide a proprioceptive feedback signal to reinforce learning through the autonomous discovery of motor constraints. Constraints are represented by a somatosensory model which is unknown beforehand to the learner. Both the sensorimotor and somatosensory system are modeled using Gaussian mixture models. We argue that using an architecture which includes a somatosensory model would reduce redundancy in the sensorimotor model and drive the learning process more efficiently than algorithms taking into account only auditory feedback. The role of this proposed system is to predict whether an undesired collision within the vocal tract under a certain motor configuration is likely to occur. Thus, compromised motor configurations are rejected, guaranteeing that the agent is less prone to violate its own constraints.

Treball desenvolupat dins el marc del programa 'European Project Semester'. The robotics facilities at Oslo and Akershus University College of Applied Sciences (HiOA) have at their disposal an autonomous humanoid robot by the name of Nao. It is a commercial product developed by SoftBank Robotics for research and educational purposes, and an international project team was assembled for the European Project Semester (EPS) program as a means of assessing its competencies and bolstering them wherever possible. The team set forth with a mission to establish meaningful interactions between the robot and his physical surroundings while placing an emphasis on humanlike behavior to the fullest extent. A goal was soon initiated for Nao to play a rule-based game against a human opponent such that his vast array of available faculties could be tested and put to use in one cohesive demonstration. Achieving this goal meant making advances in artificial intelligence,computer vision and motion planning, first as separate entities that would later converge into a singular yet multifaceted display of abilities. At the end of the project, computer vision has been implemented to the point where pattern recognition can be performed with accuracy amidst awide variety of error-prone detection scenarios. Several artificial intelligence schemes have been explored and compared quantitatively to derive performance metrics for each. Proof-ofconcept movement strategies have also been derived, and best practices for each focus area are provided as a resource for any future researchers or project groups who stand to benefit from the discoveries made in this endeavor

We present an approach for navigating in unknown environments while, simultaneously, gathering information for inspecting underwater structures using an autonomous underwater vehicle (AUV). To accomplish this, we first use our pipeline for mapping and planning collision-free paths online, which endows an AUV with the capability to autonomously acquire optical data in close proximity. With that information, we then propose a reconstruction pipeline to create a photo-realistic textured 3D model of the inspected area. These 3D models are also of particular interest to other fields of study in marine sciences, since they can serve as base maps for environmental monitoring, thus allowing change detection of biological communities and their environment over time. Finally, we evaluate our approach using the Sparus II, a torpedo-shaped AUV, conducting inspection missions in a challenging, real-world and natural scenario This work was supported by MORPH, Excellabust, and Roboacademy European projects (FP7-ICT-2011-7-288704, H2020-TWINN-2015 (CSA)-691980, and FP7-PEOPLE-2013-ITN-608096), the ARCHROV Spanish project (DPI2014-57746-C3-3-R), the Generalitat de Catalunya through the ACCIO/TecnioSpring program (TECSPR14-1-0050), and partially supported by the Colombian Government through its Predoctoral Grant Program (No. 568) offered by Colciencias

Severe disabled children have little chance of environmental and social exploration and discovery, and due to this lack of interaction and independency, it may lead to an idea that they are unable to do anything by themselves. Trying to help these children on this situation, educational robotics can offer and aid, once it can give them a certain degree of independency in exploration of environment. The system developed in this work allows the child to transmit the commands to a robot. Sensors placed on the child’s body can obtain information from head movement or muscle signals to command the robot to carry out tasks. With the use of this system, the disabled children get a better cognitive development and social interaction, balancing in a certain way, the negative effects of their disabilities.

This paper presents the new payload for Turbot, the SPARUS II AUV unit, manufactured by the University of Girona and recently acquired by the Systems, Robotics and Vision Group of the University of the Balearic Islands. The new payload has been entirely designed and integrated to host all elements necessary to perform visual 2D/3D mapping, optical (visuallaser) object reconstruction, acoustic and visual obstacle avoidance, and acoustic localization and communication. Several experiments in shallow waters of Mallorca show the validity of the sensor integration and operation for all the required tasks.

This paper shows the development of a high technical equipment to be used as tooling of submersible ROV (Remote Operated Vehicles) for offshore operations, particularly the design and fabrication by Additive Manufacturing (AM) of a Titanium Manipulator for ROVs. From the initial concept and design until a new formed company “TITANROB”, this document shortly describes the fabrication of hydraulic titanium manipulators for mid size ROV vehicles, the TitanRob series M501, G500 and the M700.

Autonomous underwater vehicles (AUVs) are routinely used to survey areas of interest in seas and oceans all over the world. However, those operations requiring intervention capabilities are still reserved to manned submersibles or remotely operated vehicles (ROVs). In the recent years, few research projects have demonstrated the viability of a new type of submersible, the intervention AUV (I-AUV), which can perform underwater missions involving manipulations in a completely autonomous way. The EU FP7 TRIDENT project is one of the most recent examples of such technological concept. This paper describes the different mechatronic components that constitute the I-AUV developed for the TRIDENT project, their hardware and software integration, and the performance of the vehicle during the project trials. Autonomous underwater vehicles (AUVs) are routinely used to survey areas of interest in seas and oceans all over the world. However, those operations requiring intervention capabilities are still reserved to manned submersibles or remotely operated vehicles (ROVs). In the recent years, few research projects have demonstrated the viability of a new type of submersible, the intervention AUV (I-AUV), which can perform underwater missions involving manipulations in a completely autonomous way. The EU FP7 TRIDENT project is one of the most recent examples of such technological concept. This paper describes the different mechatronic components that constitute the I-AUV developed for the TRIDENT project, their hardware and software integration, and the performance of the vehicle during the project trials.

Romeo as humanoid robot, which has for main goal help people who has some kind of disability, needs to be capable to grasp objects. Considering that it has led to do this first approach to grasp with Romeo. Moreover, it is wanted to grasp object which has been recognised by the RTM software (Recognition, Tracking and Modelling Objects) with a Romeo camera or an external one. This approach is included in the ROS framework as an independent package named romeo_grasper whose code is free to be shared or improved. The general idea of the approach starts with the RTM software getting the position, on camera reference, of the object, which has to be previously modelled or at least in the database. Then, this pose is transformed on robot reference and sent to MoveIt, that combined with the Rviz simulator and some ROS packages for Romeo, moves the arm of the robot to an optimal position for the grasp. Currently, it is used the IK solver from the KDL library, but here it is also explained how has been tried to implement the IKFast solver on Romeo, but without success. Finally, it is achieved to make work together all the systems, but the grasp has a some imprecision, producing that sometime it cannot be accomplish. However, in the experiments, it has been discerned where this inaccuracy comes from and it has been proposed some ways to reduce it. Furthermore, some guidelines has been set to lead Romeo to achieve a grasp using machine learning and allowing it to accomplish its goal, help the ones who need it

This article describes an exploratory study of social human-robot interaction with the experimental robotic platform MASHI. The experiences were carried out in La Bobila Cultural Center in Barcelona, Spain to study the visit

Simultaneous localization and mapping (SLAM) is an important problem to solve in robotics theory in order to build truly autonomous mobile robots. This work presents a novel method for implementing a SLAM system based on a single camera sensor. The SLAM with a single camera, or monocular SLAM, is probably one of the most complex SLAM variants. In this case, a single camera, which is freely moving through its environment, represents the sole sensor input to the system. The sensors have a large impact on the algorithm used for SLAM. Cameras are used more frequently, because they provide a lot of information and are well adapted for embedded systems: they are light, cheap and power-saving. Nevertheless, and unlike range sensors, which provide range and angular information, a camera is a projective sensor providing only angular measurements of image features. Therefore, depth information (range) cannot be obtained in a single step. In this case, special techniques for feature system-initialization are needed in order to enable the use of angular sensors (as cameras) in SLAM systems. The main contribution of this work is to present a novel and robust scheme for incorporating and measuring visual features in filtering-based monocular SLAM systems. The proposed method is based in a two-step technique, which is intended to exploit all the information available in angular measurements. Unlike previous schemes, the values of parameters used by the initialization technique are derived directly from the sensor characteristics, thus simplifying the tuning of the system. The experimental results show that the proposed method surpasses the performance of previous schemes.

This paper reflects the state of art in the field of human factors for unmanned aerial vehicles. It describes the GEDIS-UAV guide, which is a mod- ification of the GEDIS guide. It also shows the evaluation of the Sky-eye project graphical user interface as an example of the methodology. The analy- sis and evaluation method reflected in this paper may be used to improve the graphical user interface of any unmanned aerial vehicle.

A major focus for children’s quality of life programs in hospitals is improving their experiences during procedures. In anticipation of treatment, children may become anxious and during procedures pain appears. The aim of this article is to introduce a proposal to design pioneering techniques based on the use of social robots to improve the patient experience by eliminating or minimizing pain and anxiety. According to this proposed challenge, this research aims to design and develop specific human-social robot interaction with pet robots. Robot interactive behavior will be designed based on modular skills using soft-computing paradigms.

This work deals with the problem of planning the movements of a two-hand system in order to grasp an object with one hand and using the other to remove potential obstacles. The approach is based on a Probabilistic Road Map that does not rule out samples with collisions with removable objects but instead classifies them according to the collided obstacle(s), and allows the search of free paths with the indication of which objects must be removed from the work-space to make the path be valid. The approach has been implemented and some examples are presented in this work.

An exportable and robust system using only camera images is proposed for path execution in robot navigation. Motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames, so the method is called SURF flow. This information is used to correct robot displacement when a straight forward path command is sent to the robot, but it is not really executed due to several robot and environmental concerns. The proposed system has been successfully tested on the legged robot Aibo.

PFC del programa Erasmus elaborat a Nottingham Trent University From the beginning of Humanity the society has tried to find a solution to any kind of necessity. Because of that the technology was invented. Technology was invented to satisfy the people necessities. In the twenty-first century, has been trying to mix the medicine with technology to produce, through the interaction of the technological and medical advances, unexpected solutions for the human being in the following years. Through the technology has reached to develop a new type of material with a kind of special features, the Shape Memory Alloy. These materials have characteristics which make them very special. Their shape can be changed or deformed but, when heat is applied to them, they come back to their original shape. This property is so interesting which has made think about the possibility of using these materials for medical innovations. The main objective of the project described below is making a mechanical finger to be actuated by these materials. In this way, being performed for the Shape Memory Alloy, is not necessary having electronic components inside the finger because it is actuated by mechanical principles of tension. Therefore, the project cost drops dramatically and in the near future is possible the mechanical finger could be used for current people who need it. In this project is also interesting to see the entire process of design and product development, from the approach of the idea until the final assembly of the project, including design and production of the model.

To explore social bonds’ emergence with robots, a field study with 49 sixth grade scholars (aged 11-12 years) and 4 different robots was carried out at an elementary school. A subsequent laboratory experiment with 4 of the participants was completed in order to explore social engagement. At school, children’s preferences, expectations on functionality and communication, and interaction behavior were studied. In the lab, recognition, partner’s selection, and dyadic interaction were explored. Both at school and in the lab, data from videotaped direct observation, questionnaires and interviews were gathered. The results showed that different robots’ appearance and performance elicit in children distinctive perceptions and interactive behavior and affect social processes (e. g., role attribution and attachment). The preliminary results will help in the design of robot-based programs for hospitalized children to improve quality of life1

This work presents an intergated strategy for planning and learning suitable to execute tasks with robotic platforms without any previous task specification. The approach rapidly learns planning operators from few action experiences using a competitive strategy where many alternatives of cause-effect explanations are evaluated in parallel, and the most successful ones are used to generate the operators. The system operates without task interruption by integrating in the planning-learning loop a human teacher that supports the planner in making decisions. All the mechanisms are integrated and synchronized in the robot using a general decision-making framework.

When unmanned underwater vehicles (UUVs) perform missions near the ocean floor, optical sensors can be used to improve local navigation. Video mosaics allow to efficiently process the images acquired by the vehicle, and also to obtain position estimates. We discuss in this paper the role of lens distortions in this context, proving that degenerate mosaics have their origin not only in the selected motion model or in registration errors, but also in the cumulative effect of radial distortion residuals. Additionally, we present results on the accuracy of different feature-based approaches for self-correction of lens distortions that may guide the choice of appropriate techniques for correcting distortions.

Un dels principals problemes de la interacció dels robots autònoms és el coneixement de l'escena. El reconeixement és fonamental per a solucionar aquest problema i permetre als robots interactuar en un escenari no controlat. En aquest document presentem una aplicació pràctica de la captura d'objectes, de la normalització i de la classificació de senyals triangulars i circulars. El sistema s'introdueix en el robot Aibo de Sony per a millorar-ne la interacció. La metodologia presentada s'ha comprobat en simulacions i problemes de categorització reals, com ara la classificació de senyals de trànsit, amb resultats molt prometedors. Uno de los principales problemas de la interacción de los robots autónomos es el conocimiento de la escena. El reconocimiento es fundamental para solventar este problema y permitir a los robots interactuar en un escenario no controlado. En este documento, presentamos una aplicación práctica de captura del objeto, normalización y clasificación de señales triangulares y circulares. El sistema es introducido en el robot Aibo de Sony para mejorar el comportamiento de la interacción del robot. La metodología presentada ha sido testeada en simulaciones y problemas de categorización reales, como es la clasificación de señales de tráfico, con resultados muy prometedores. One of the main problems of autonomous robots interaction is the scene knowledge. Recognition is concerned to deal with this problem and to allow robots to interact in uncontrolled environments. In this paper, we present a practical application for object fitting, normalization and classification of triangular and circular signs. The system is introduced in the Aibo robot of Sony to increase the robot interaction behaviour. The presented methodology has been tested in real simulations and categorization problems, as the traffic signs classification, with very promising results. Nota: Aquest document conté originàriament altre material i/o programari només consultable a la Biblioteca de Ciència i Tecnologia.

This paper addresses the problem of object recognition from colorless 3D point clouds in underwater environments. It presents a performance comparison of state-of-the-art global descriptors, which are readily available as open source code. The studied methods are intended to assist Autonomous Underwater Vehicles (AUVs) in performing autonomous interventions in underwater Inspection, Maintenance and Repair (IMR) applications. A set of test objects were chosen as being representative of IMR applications whose shape is typically known a priori. As such, CAD models were used to create virtual views of the objects under realistic conditions of added noise and varying resolution. Extensive experiments were conducted from both virtual scans and from real data collected with an AUV equipped with a fast laser sensor developed in our research centre. The underwater testing was conducted from a moving platform, which can create deformations in the perceived shape of the objects. These effects are considerably more difficult to correct than in above-water counterparts, and therefore may affect the performance of the descriptor. Among other conclusions, the testing we conducted illustrated the importance of matching the resolution of the database scans and test scans, as this significantly impacted the performance of all descriptors except one. This paper contributes to the state-of-the-art as being the first work on the comparison and performance evaluation of methods for underwater object recognition. It is also the first effort using comparison of methods for data acquired with a free floating underwater platform This work was supported by the Spanish Government through a FPI Ph.D. grant to K. Himri, as well as by the Spanish Project DPI2017-86372-C3-2-R (TWINBOT-GIRONA1000) and the H2020-INFRAIA-2017-1-twostage-731103 (EUMR)

This paper presents a method to build a semantic map to assist an underwater vehicle-manipulator system in performing intervention tasks autonomously in a submerged man-made pipe structure. The method is based on the integration of feature-based simultaneous localization and mapping (SLAM) and 3D object recognition using a database of a priori known objects. The robot uses Doppler velocity log (DVL), pressure, and attitude and heading reference system (AHRS) sensors for navigation and is equipped with a laser scanner providing non-coloured 3D point clouds of the inspected structure in real time. The object recognition module recognises the pipes and objects within the scan and passes them to the SLAM, which adds them to the map if not yet observed. Otherwise, it uses them to correct the map and the robot navigation if they were already mapped. The SLAM provides a consistent map and a drift-less navigation. Moreover, it provides a global identifier for every observed object instance and its pipe connectivity. This information is fed back to the object recognition module, where it is used to estimate the object classes using Bayesian techniques over the set of those object classes which are compatible in terms of pipe connectivity. This allows fusing of all the already available object observations to improve recognition. The outcome of the process is a semantic map made of pipes connected through valves, elbows and tees conforming to the real structure. Knowing the class and the position of objects will enable high-level manipulation commands in the near future This work was supported by the Spanish Government through a FPI Ph.D. grant to K. Himri, as well as by the Spanish Project DPI2017-86372-C3-2-R (TWINBOT-GIRONA1000) and the European project H2020-INFRAIA-2017-1-twostage-731103 (EUMarineRobots)

Underwater inspection, maintenance and repair (IMR) operations are being increasingly robotized in order to reduce safety issues and costs. These robotic systems rely on vision sensors to perform fundamental tasks, such as navigation and object recognition and manipulation. Especially, active optical 3D scanners are commonly used due to the domain-specific challenges of underwater imaging. This paper presents an exhaustive survey on the state of the art of optical 3D underwater scanners. A literature review on light projection and light-sensing technologies is presented. Moreover, quantitative performance comparisons of underwater 3D scanners present in the literature and commercial products are carried out This research was funded by the GIRONA1000 project (grant number DPI2017-86372-C3-2-R, by the Spanish Ministry of Science) and EUMR project (grant number H2020-INFRAIA-2017-1-twostage-731103, by the European Commission).