Urzua, S.; Munguia, R.F.; Grau, A. Journal of intelligent and robotic systems: theory and applications (Online) Vol. 2018, p. 1-15 DOI: 10.1007/s10846-018-0775-y Data de publicació: 2018-02-02 Article en revista
A typical navigation system for a Micro Aerial Vehicle (MAV) relies basically on GPS for position estimation. However,for several kinds of applications, the precision of the GPS is inappropriate or even its signal can be unavailable. In this context, and due to its flexibility, Monocular Simultaneous Localization and Mapping (SLAM) methods have become a good alternative for implementing visual-based navigation systems for MAVs that must operate in GPS-denied environments.
On the other hand, one of the most important challenges that arises with the use of the monocular vision is the difficulty to recover the metric scale of the world. In this work, a monocular SLAM system for MAVs is presented. In order to overcome the problem of the metric scale, a novel technique for inferring the approximate depth of visual features from an ultrasonic range-finder is developed. Additionally, the altitude of the vehicle is updated using the pressure measurements of a barometer. The proposed approach is supported by the theoretical results obtained from a nonlinear observability test.
Experiments performed with both computer simulations and real data are presented in order to validate the performance of the proposal. The results confirm the theoretical findings and show that the method is able to work with low-cost sensors.
The objective of this paper is to explain the importance of research in wastewater transportation (sewage systems) using new technologies such as robotics systems and information and communication technologies. ECHORD++ (European Coordination Hub for Open Robotics Development) is a very useful tool to foster this research and to meet needs and solutions. In this paper, authors explain the tool as well as the methodology to promote robotics research in urban environments, and the on-going experience will demonstrate that huge advances are made in this field.
Grau, A.; Indri, M.; Lo Bello, L.; Sauter, T. Annual Conference of the IEEE Industrial Electronics Society p. 6159-6164 DOI: 10.1109/IECON.2017.8217070 Data de presentació: 2017-10-30 Presentació treball a congrés
Robotics is a surprisingly old discipline, and robots have shaped industry and the various industrial revolutions for many decades. This paper covers topics relevant to the IES Technical Committee on Factory Automation, focusing in particular on the evolution of industrial robotics. After providing a historical perspective on the topic, the paper addresses current and future trends, revealing the close link between the progress in industrial robotics and the parallel evolution of industrial communication systems, which represent an enabling technology for modern industrial robotics.
The idea of the ECHORD project was born before the economic crisis had its maximum impact on the robotics industry. Therefore, the concept of a project with the clear goal to strengthen the collaboration between academia and industry was a good opportunity to support the industry by offering funding opportunities and fostering already existing networks and creating new partnerships with the academic world taking into account the circular economy in the productive cycle of the intelligent robotics solutions to solve the challenges of the modern cities. One of the most innovative part of this project is to foster the participation of public investment in new robotic projects mainly in urban robotics. At this moment, more than 40 european cities have been participating in the challenge that ECHORD++ proposed.
In this paper, a novel algorithm to know the pose of any autonomous vehicle is described. Such a system (Attitude and Heading Reference System, AHRS) is essential for real time vehicle navigation, guidance and control applications. For low funded projects, with simple sensors, efficient and robust algorithms become necessary for an acceptable performance, and the well-known extended Kalman filter (EKF) fulfills those requirements. In this kind of applications, the use of the EKF in direct configuration has been much less explored than its counterpart, the EKF in indirect configuration. Specifically, in this paper a novel method based on an Extended Kalman Filter in direct configuration is proposed, where the filter is explicitly derived from both kinematic and errors models. Experiments with real data show that the proposed method is able to maintain an accurate and drift-free attitude and heading estimation.
This chapter describes the development of an autonomous fluid sampling system for outdoor facilities, and the localization solution to be used. The automated sampling system will be based on collaborative robotics, with a team of a UAV and a UGV platform travelling through a plant to collect water samples. The architecture of the system is described, as well as the hardware present in the UAV and the different software frameworks used. A visual simultaneous localization and mapping (SLAM) technique is proposed to deal with the localization problem, based on authors’ previous works, including several innovations: a new method to initialize the scale using unreliable global positioning system (GPS) measurements, integration of attitude and heading reference system (AHRS) measurements into the recursive state estimation, and a new technique to track features during the delayed feature initialization process. These procedures greatly enhance the robustness and usability of the SLAM technique as they remove the requirement of assisted scale initialization, and they reduce the computational effort to initialize features. To conclude, results from experiments performed with simulated data and real data captured with a prototype UAV are presented and discussed.
Pollution in coastal areas is very hazardous for population. The problem is even higher when this pollution occurs in bathing areas such as beaches in populated areas. In this work we present a new automatic control application for wastewater plants when pollution is caused by those plants because there is an excess of water to be treated and it is thrown to the sea with high levels of biological pollutants (bacteria...). Those problems can be aggravated if climatic conditions pull to the coastal area the untreated water without the cleaning action of sea water. The experimentation is done with real data and real conditions in Barcelona area, at Mediterranean sea, with the urban wastewater plant of Besòs
El problema de Localización y Mapeado Simultáneos (SLAM) es ampliamente reconocido como uno de los desafíos fundamentales a resolver en los campos de percepción y robótica autónomas para llegar a producir agentes robóticos móviles. El problema en si trata de como un robot podría, en un entorno a priori desconocido, construir un mapa con la información disponible vía sus sensores, y localizarse y navegar con respecto a este mismo mapa, estimando su posición.La importancia de este problema, junto con la gran variedad de estrategias y la complejidad de los subproblemas que plantean, hace que el campo de SLAM sea una de las áreas más activas de investigación en robótica. Uno de los mayores desafíos dentro del campo de SLAM, que comparte con otros ámbitos de la robótica y la percepción autónoma, es el problema de Asociación de Datos (data association, DA); ya que normalmente implica un precario equilibrio entre la eficacia y robustez de los resultados obtenidos, y la potencia y tiempo de cálculos necesarios para llegar a ellos, siendo un factor determinante en muchas estrategias de SLAM.En cuanto a sensores usados, el campo ha sido dominado por telémetros de barrio, pero durante la última década la investigación en SLAM visual produjo estrategias de gran impacto. Esto se debe en gran medida a que la demanda para el consumo de sensores de cámara ha incrementado sus prestaciones y bajado sus precios. La cámara, como sensor, produce mediciones de intensidad lumínica sobre puntos proyectados en orientaciones conocidas, que pueden convertirse en mediciones sobre características visuales aplicando métodos de visión por computador. Estas características visuales suelen ser puntos, pero pueden presentar múltiples niveles de complejidad.La misma demanda de los mercados ha impulsado el desarrollo de sensores micro-electro-mecánicos y otros dispositivos robóticos que han contribuido a desarrollar la robótica colaborativa y las tecnologías de dispositivos vestibles (wearable). Éstas tecnologías han abierto muchos campos de investigación dentro del problema de SLAM, como por ejemplo el SLAM colaborativo y el basado en interacción robot-humano (human-robot interaction, HRI).Esta tesis se centra en el estudio y desarrollo de un método de SLAM visual basado en la técnica delayed inverse depth feature initialization monocular SLAM (DI-D monocular SLAM), que pueda integrarse en un marco de SLAM colaborativo con interacción robot-humano. Con éste fin la investigación se ha centrado en dos áreas distintas. Primeramente la técnica DI-D SLAM ha sido estudiada y analizada, revisando sus procesos y algoritmos, con énfasis en el problema de asociación de datos. El estudio del problema de DA ha dado lugar a un nuevo algoritmo de validación para asociación de datos, que permite evitar información espuria y hacer al proceso más robusto.Una vez analizado y actualizado el método DI-D SLAM, se procede a introducir el marco de colaboración HRI, enfocándolo inicialmente en resolver uno de los inconvenientes del método de SLAM: el requisito de introducir parte del mapa a priori para mantener la estimación de la escala. Para introducir la colaboración HRI se emplea un dispositivo vestible que incorpora una cámara secundaria y otros sensores. La información de esta cámara secundaria, cuya pose con respecto a la cámara de SLAM principal es aproximadamente conocida, permite acelerar la introducción de características en el método DI-D SLAM y evitar el requisito de inicializar la escala del mapa.La introducción del método de percepción colaborativa permitido expandir sus beneficios a otras partes y problemas del método DI-D SLAM. Para ello se integró por completo en el proceso de medida y corrección del filtro de Kalman extendido (EKF) usado, tratando la medición colaborativa como un sensor virtual. Para poder evaluar cómo influye el comportamiento sistema HRI se derivaron varias métricas nuevas, que fueron estudiadas con una batería de secuencias experimentales.
The Simultaneous Localization and Mapping (SLAM) problem is widely acknowledged as one of the fundamental problem to solve in perception and robotics to produce actual mobile robotic agents. The problem itself is that of how can a mobile robot agent operate in an a priori unknown environment, using the sensory systems available (normally on itself) to perceive its surroundings, build a map with this knowledge, and localize itself in said map tracking its own position.
This relevance, combined with the diversity of approaches available to solve it, and the depth of the challenges it presents, makes the SLAM problem one of the more active areas of research in robotics. One of the most complex challenges in any approach is the data association, as it generally conveys hard a trade-off between robustness and computational time required, and can impact the whole architecture of a SLAM method.
In terms of sensors used, the field was originally dominated by range finder sensors, but visual SLAM research has grown in popularity in the last decade. Camera sensors have been expanding its capabilities and specifications thanks to the consumer demand for them. As a sensor, they provide lightning measurements of the projected points at known bearings, which through computer vision can be converted into bearing measurements for visual features, which can be themselves of several levels of complexity.
The same consumer demand has also pushed technical developments in MEMS and robotic devices with a direct impact in the field of cooperative robotics and the emergence of wearable device technology, where human can wear or carry devices with several sensors in an unobtrusive way. These technologies have opened many opportunities in for research in robotics, including the field of collaborative SLAM and the area of human-robot interaction (HRI).
This thesis is focused in the study and development of a visual SLAM methodology based on the delayed inverse-depth feature initialization (DI-D) monocular SLAM which can benefit and exploit the advantages of working in a HRI collaborative framework. In order to achieve this, the research is focused in two different areas. Firstly, the known and tested DI-D monocular SLAM is studied: its procedures and algorithms detailed and analyzed; with emphasis in the data association problem (DA). The DA process is reviewed, and a new validation algorithm is introduced to strengthen and give robustness to the data association technique used.
Once the DI-D has been studied and updated the HRI collaborative framework is introduced, with an initially focus into solving one of its inconveniences: the requirement of a scaled metric initialization with a priori knowledge. The HRI is introduced by deploying into a human being a custom built wearable device which includes a camera and some other sensors. The data from this secondary monocular sensor, whose pose is approximately known with respect to the camera used to solve the SLAM problem, allows speeding up the feature initialization process of the DI-D, and even ignoring the requirement of scale initialization.
As the introduction of the HRI framework was successful, its advantages were further expanded to the rest of the SLAM process, including the measurement and update steps. This integration was performed based in a virtual sensor methodology, where the collaborative measurement process was treated as a single sensor with its specifications, allowing seamless fusion into the EKF-SLAM (Extended Kalman Filter SLAM). To evaluate the specific impact of the HRI with respect to the behaviour of the secondary camera, several new metrics have been proposed and studied.
All the methods have been proved and validated through experimentation with real data. When it was found relevant, the experiments were evaluated in real-time scenarios, and several simulations have been included when needed to prove some theoretical hypothesis.
El problema de Localización y Mapeado Simultáneos (SLAM) es ampliamente reconocido como uno de los desafíos fundamentales a resolver en los campos de percepción y robótica autónomas para llegar a producir agentes robóticos móviles. El problema en si trata de como un robot podría, en un entorno a priori desconocido, construir un mapa con la información disponible vía sus sensores, y localizarse y navegar con respecto a este mismo mapa, estimando su posición. La importancia de este problema, junto con la gran variedad de estrategias y la complejidad de los subproblemas que plantean, hace que el campo de SLAM sea una de las áreas más activas de investigación en robótica. Uno de los mayores desafíos dentro del campo de SLAM, que comparte con otros ámbitos de la robótica y la percepción autónoma, es el problema de Asociación de Datos (data association, DA); ya que normalmente implica un precario equilibrio entre la eficacia y robustez de los resultados obtenidos, y la potencia y tiempo de cálculos necesarios para llegar a ellos, siendo un factor determinante en muchas estrategias de SLAM. En cuanto a sensores usados, el campo ha sido dominado por telémetros de barrio, pero durante la última década la investigación en SLAM visual produjo estrategias de gran impacto. Esto se debe en gran medida a que la demanda para el consumo de sensores de cámara ha incrementado sus prestaciones y bajado sus precios. La cámara, como sensor, produce mediciones de intensidad lumínica sobre puntos proyectados en orientaciones conocidas, que pueden convertirse en mediciones sobre características visuales aplicando métodos de visión por computador. Estas características visuales suelen ser puntos, pero pueden presentar múltiples niveles de complejidad. La misma demanda de los mercados ha impulsado el desarrollo de sensores micro-electro-mecánicos y otros dispositivos robóticos que han contribuido a desarrollar la robótica colaborativa y las tecnologías de dispositivos vestibles (wearable). Éstas tecnologías han abierto muchos campos de investigación dentro del problema de SLAM, como por ejemplo el SLAM colaborativo y el basado en interacción robot-humano (human-robot interaction, HRI). Esta tesis se centra en el estudio y desarrollo de un método de SLAM visual basado en la técnica delayed inverse depth feature initialization monocular SLAM (DI-D monocular SLAM), que pueda integrarse en un marco de SLAM colaborativo con interacción robot-humano. Con éste fin la investigación se ha centrado en dos áreas distintas. Primeramente la técnica DI-D SLAM ha sido estudiada y analizada, revisando sus procesos y algoritmos, con énfasis en el problema de asociación de datos. El estudio del problema de DA ha dado lugar a un nuevo algoritmo de validación para asociación de datos, que permite evitar información espuria y hacer al proceso más robusto. Una vez analizado y actualizado el método DI-D SLAM, se procede a introducir el marco de colaboración HRI, enfocándolo inicialmente en resolver uno de los inconvenientes del método de SLAM: el requisito de introducir parte del mapa a priori para mantener la estimación de la escala. Para introducir la colaboración HRI se emplea un dispositivo vestible que incorpora una cámara secundaria y otros sensores. La información de esta cámara secundaria, cuya pose con respecto a la cámara de SLAM principal es aproximadamente conocida, permite acelerar la introducción de características en el método DI-D SLAM y evitar el requisito de inicializar la escala del mapa. La introducción del método de percepción colaborativa permitido expandir sus beneficios a otras partes y problemas del método DI-D SLAM. Para ello se integró por completo en el proceso de medida y corrección del filtro de Kalman extendido (EKF) usado, tratando la medición colaborativa como un sensor virtual. Para poder evaluar cómo influye el comportamiento sistema HRI se derivaron varias métricas nuevas, que fueron estudiadas con una batería de secuencias experimentales.
Wastewater plants, mainly with secondary treatments, discharge polluted water to environment that cannot be used in any human activity. When those dumps are in the sea it is expected that most of the biological pollutants die or almost disappear before water reaches human range. This natural withdrawal of bacteria, viruses and other pathogens is due to some conditions such as the salt water of the sea and the sun effect, and the dumps areas are calculated taking into account these conditions. However, under certain meteorological phenomena water arrives to the coast without the full disappearance of pollutant elements. In Mediterranean Sea there are some periods of adverse climatic conditions that pollute the coast near the wastewater dumping. In this paper, authors present an automatic control that prevents such pollution episodes using two mathematical models, one for the pollutant transportation and the other for the pollutant removal in wastewater spills
The objective of this article is to present a specific urban challenge proposed by European cities in ECHORD++ project that can be the starter point of new innovative public procurements. The project that was selected by the project leading team has been a robotic solution for monitoring the sewage system of a European city. Cities are prepared and the Research and Technological Development (RTD) consortia are waiting for real opportunities. The take-off of the robotic technology could be possible: from Lab to Market addressing real urban needs of citizens and cities. The proposals obtained in ECHORD++ could be followed by other cities.
Using a camera, a micro aerial vehicle (MAV) can perform visual-based navigation in periods or circumstances when GPS is not available, or when it is partially available. In this context, the monocular simultaneous localization and mapping (SLAM) methods represent an excellent alternative, due to several limitations regarding to the design of the platform, mobility and payload capacity that impose considerable restrictions on the available computational and sensing resources of the MAV. However, the use of monocular vision introduces some technical difficulties as the impossibility of directly recovering the metric scale of the world. In this work, a novel monocular SLAM system with application to MAVs is proposed. The sensory input is taken from a monocular downward facing camera, an ultrasonic range finder and a barometer. The proposed method is based on the theoretical findings obtained from an observability analysis. Experimental results with real data confirm those theoretical findings and show that the proposed method is capable of providing good results with low-cost hardware.
At the Engineering School of Barcelona (ETSEIB- UPC) a multimedia pedagogical tool has been developed in order to traini ng concepts and ecojustice, environmentalism and sustainability to the students in Technical degrees, specifically in Robotics Engineering. This didactical tool consists in a serial of multimedia world maps that describes the world situation in a wide range of different trends such as the nuclear energy, the fossil fuels, the electronic components of the machines, the atomic weapons, etc. The developed pedagogical instrument uses a slide presentation format in order to integrate the relevant information of different economical-environmental- social themes related with actual society. In this paper one of the multimedia maps is explained and discussed: the nuclear energy map. This pedagogical resource boosts the reflection in our students about several aspects of social interest in a sustainable overview and students are able to understand the role of Robotics in many and relevant applications.
In the not-too-distant past, robots were only used in the automation industry, but in some recent years the scientific community turned its attention to applications where the objective was not merely the increase of productivity and effectiveness. Those new applications focus in yielding useful services to humans requiring robots with features complete ly different to the industrial robots developed so far; these new robo ts are called “service robots”. Service robotics has become a main axis in research at international level, and nowadays the number of robots used in people’s assistance, surgery, therapy, services, education and entertainment has been growing. In this work authors will focus in Robotics regarding the teaching/learning processes. Robotics can be used not only as a subject of study but as a support tool that facilitates the learning process by inquiry providing an easy approach to the concepts. In general, robotics is a great pedagogical tool and it is very important to take advantage of the motivation that generates among the students the fact of interacting with a robot to introduce concepts in an easy and didactical way such as computation, electronics, physics, mechanics and mathematics. There exists a great variety of educational robotic kits to be used in the classroom, such as RoboCub, Qrio, Robonova, etc. Most of these kits are oriented to robot building and programming as well. It is well worth to remark that in engineering simulations play an important role because is the first stage in the design process and it has to be used before the implementation stage in order to guarantee the efficiency and performance of any system. Thanks to simulation is not only possible to know a priori how a particular robotic configuration evolves but also allows implementing functions and algorithms. This fact will permit students to be introduced in the programming world as well as in the learning of more theoretical concepts such as kinematics, dynamics, control, robot navigation, locomotion... from a more practical, visual point of view connecting students with the real world. Some of the most popular simulators in humanoid robotics are: Webots, SimRobot, Gazebo, SimPark, among others. The main problem with the existing simulators is that they are not freely available in the mar ket and they have an unaffo rdable cost per license for the educational centres and researcher s. Moreover, in many cases, those simulators do not fit exactly with the available equipment in the robotics labs and for those reasons and for the sake of the innovation authors propose the development of their own simulator th at is adapted to their robotics lab equipment. This experience can be adapted to any robotics lab configuration. In this work a new software interface has been developed in order to introduce Humanoid Robotics to the students in their initial courses of engineering. This simulator is under test and assessment in the Robotics subject at the Industrial Engineering degree during this academic year. This work expects to be an illustrative example to implement software interfaces according to the robot availability in each robotics lab
Fukushima disaster changed the mind of many people and original ideas have to be rethought, nuclear energy seems not to be the ideal solution for a clean, emission-free energy production. It is higher education’s responsibility to integrate current social aspects in technical degrees. From Technical University of Catalonia an interactive didactic tool has been developed in order to training social concepts inside engineering subjects. The pedagogical resource developed uses a slide presentation format in order to integrate the relevant information of different economical-environmental-social themes related with actual society. In this work authors will explain how this innovative tool is used to taught Robotics subject at the Industrial Electronics and Automatic Control degree. Specifically, the nuclear map will be used to the aim of raise awareness the students of the role of the energy, the economy and the sustainability in robotic applications. This multimedia resource allows the social reflection of our students through the critical thinking.
Cities present new challenges and needs to satisfy and improve lifestyle for their citizens under the concept “Smart City”. In order to achieve this goal in a global manner, new technologies are required as the robotic one. But Public entities unknown the possibilities offered by this technology to get solutions to their needs. In this paper the development of the Innovative Public Procurement instruments is explained, specifically the process PDTI (Public end Users Driven Technological Innovation) as a driving force of robotic research and development and offering a list of robotic urban challenges proposed by European cities that have participated in such a process. In the next phases of the procedure, this fact will provide novel robotic solutions addressed to public demand that are an example to be followed by other Smart Cities.
In recent years, many researchers have addressed the issue of making Unmanned Aerial Vehicles (UAVs) more and more autonomous. In this context, the state estimation of the vehicle position is a fundamental necessity for any application involving autonomy. However, the problem of position estimation could not be solved in some scenarios, even when a GPS signal is available, for instance, an application requiring performing precision manoeuvres in a complex environment. Therefore, some additional sensory information should be integrated into the system in order to improve accuracy and robustness. In this work, a novel vision-based simultaneous localization and mapping (SLAM) method with application to unmanned aerial vehicles is proposed. One of the contributions of this work is to design and develop a novel technique for estimating features depth which is based on a stochastic technique of triangulation. In the proposed method the camera is mounted over a servo-controlled gimbal that counteracts the changes in attitude of the quadcopter. Due to the above assumption, the overall problem is simplified and it is focused on the position estimation of the aerial vehicle. Also, the tracking process of visual features is made easier due to the stabilized video. Another contribution of this work is to demonstrate that the integration of very noisy GPS measurements into the system for an initial short period of time is enough to initialize the metric scale. The performance of this proposed method is validated by means of experiments with real data carried out in unstructured outdoor environments. A comparative study shows that, when compared with related methods, the proposed approach performs better in terms of accuracy and computational time.
Guerra, E.; Bolea, Y.; Grau, A.; Munguia, R.F.; Gamiz, J. Annual Conference of the IEEE Industrial Electronics Society p. 6853-6858 DOI: 10.1109/IECON.2016.7793683 Data de presentació: 2016-10-27 Presentació treball a congrés
This work presents a solution to automatize the water sampling process of outdoor basins in a wastewater treatment plant. The system proposed is based on the utilization of collaborative robotics: a team of an UAV and a terrestrial robotic platform make a route along the plant collecting and storing the water samples. The architecture of the designed system is described in terms of functional blocks, and implementation details including software frameworks and hardware on the UAV are provided. As the objective of the system is industry levels of robustness and performance, the UAV use is minimized and subjected to control from the robotic ground platform, reducing risks associated with autonomous UAV. To conclude, results from experiments performed to validate the viability of the system and study several design decisions are presented and briefly discussed, including: estimation of the accuracy of several GNSS technologies on the plant, viability of the landing operation over a mobile robotic platform and controlling a quadrotor over waters.
Mobile robots can be used in many different applications, including mapping, search, rescue, reconnaissance, hazard detection, and carpet cleaning, exploration, etc. However, they are limited due to their reliance on traditional energy sources such as electricity and oil which cannot always provide a convenient energy source in all situations. In an ever more eco-conscious world, solar energy offers the most environmentally clean option of all energy sources. Electricity presents threats of pollution resulting from its production process, and oil poses a huge threat to the environment. Not only does it pose harm by the toxic emissions (for instance CO2 emissions), it produces the combustion process necessary to produce energy, but there is the ever present risk of oil spillages and damages to ecosystems. Solar energy can help to mitigate carbon emissions by replacing more carbon intensive sources of heat and power. The challenge of this work is to propose the design and the implementation of electric battery recharge stations. Those recharge docks are based on the use of renewable energy such as solar energy (with photovoltaic panels) with the object to reduce the CO2 emissions. In this paper, a comparative study of the CO2 emission productions (from the use of different energy sources: natural gas, gas oil, fuel and solar panels) in the charging process of the Segway PT batteries is carried out. To make the study with solar energy, a photovoltaic panel, and a Buck-Boost DC/DC block has been used. Specifically, the STP005S-12/Db solar panel has been used to carry out our experiments. This module is a 5Wp-photovoltaic (PV) module, configured with 36 monocrystalline cells serially connected. With those elements, a battery recharge station is made to recharge the robot batteries. For the energy storage DC/DC block, a series of ultracapacitors have been used. Due to the variation of the PV panel with the temperature and irradiation, and the non-integer behavior of the ultracapacitors as well as the non-linearities of the whole system, authors have been used a fractional control method to achieve that solar panels supply the maximum allowed power to recharge the robots in the lesser time. Greenhouse gas emissions for production of electricity vary due to regional differences in source fuel. The impact of an energy technology on the climate can be characterised by its carbon emission intensity, a measure of the amount of CO2, or CO2 equivalent emitted by unit of energy generated. In our work, the coal is the fossil energy more hazardous, providing a 53% more of gas emissions than natural gas and a 30% more than fuel. Moreover, it is remarkable that existing fossil fuel technologies produce high carbon emission intensity through the combustion of carbon-rich fuels, whilst renewable technologies such as solar produce little or no emissions during operation, but may incur emissions during manufacture. The solar energy thus can help to mitigate carbon emissions.
This book brings together some recent advances and development in robotics. In 12 chapters, written by experts and researchers in respective fields, the book presents some up-to-date research ideas and findings in a wide range of robotics, including the design, modeling, control, learning, interaction, and navigation of robots. From an application perspective, the book covers UAVs, USVs, mobile robots, humanoid robots, graspers, and underwater robots. The unique text offers practical guidance to graduate students and researchers in research and applications in the field of robotics.
Guerra, E.; Munguia, R.F.; Bolea, Y.; Grau, A. IEEE International Conference on Industrial Informatics p. 219-224 DOI: 10.1109/INDIN.2016.7819162 Data de presentació: 2016-07-21 Presentació treball a congrés
A complete approach to the visual localization and mapping problem (SLAM) is presented in this work. The presented approach exploits the enhanced capabilities of a system where a human and a robot collaborate in surveying/exploratory tasks. The human is supposed to wear a smart headwear device, which deploys a inertial measurement unit and a camera, Hv. This camera acts as a secondary sensor, and provides data to the robotic Rv camera performing mapping tasks. The data from the human-worn camera is used to produce real-time depth estimation of landmarks when its field of view overlaps with that of Rv. These measurements are mathematically fully integrated into the EKF-SLAM methodology. Experiments with real captured data validate the proposed approach.
A purification water plant is a hydraulic system that needs an automation control to achieve an effective and sustainable management taking into account the water resource preservation. The World Health Organisation Drinking Water Guidelines (WHO, 1993) provides an appropriate context for the subject matter covered: “Disinfection is unquestionably the most important step in the treatment of water for public supply. The destruction of microbiologic al pathogens is essential and almost invariably involves the use of reactive agents such as chlorine, which are not only powerful biocides but also capable of reacting with other water constituents to form new compounds with potentially long-term health effects”. Chlorine dosing is one of the essential treatment processes in purification water plant because chlorine has been the most commonly used disinfectant for the last hundred years. Chlorine reacts with natural organic matter in water to form DBP’s (disinfection by products), and researchers are becoming increasingly concerned about the health problems those products can cause. This fact highlights the sensitivity of the chlorination process, and the importance of having a reliable accurate control system to ensure that the amount of chlorine dosed in drinking water is correct.
For this reason, in this paper a novel automated chlorination process is proposed. This process has three main features: variable dynamics (the behaviour of the plant is nonlinear and with unlumped parameters) and variable large delay (because there is a delay between the input chlorine concentration and the output chlorine concentration due to the contaminant transport), and sudden and undesired appearance of ammonium in the treated water due to chlorination. The variation of the plant parameters (dynamic and delay) in the plant operation range is caused by the variation of inflow chlorine. These features lead to the development of parameter time variable control model and to the design of a parameter time variable controller. The global control model is built from the combination of the identified local models (in each operating point, a fraction of the operation range of the plant) by classical identification tehniques. A variable Smith Predictor scheme is used with the goal to cancel the large variable delay. The control scheme is based on a feedback using a PI (Proportional-Integral) switched according to inflow concentration variability. On the other hand to counteract the ammonium effect appearance a feedforward configuration is used. The establishment of this new control methodology has represented a significant change in the operation of the plant providing a better water quality and chlorine saving. This methodology has been applied at the purification water plant in Sant Joan Despí (Barcelona, Spain)
Sewer inspections require many people to work in risky and unhealthy conditions. A European ECHORD++ project introduces a robotic solution in this process aiming to reduce the labour risks, improving the precision of sewer inspections and optimizing sewer cleaning resources of cities. This system should be able to determine the state of the sewer in order to identify sewer segments where its functionality has been reduced either by sediments or by structural defects. Other functionalities required are sewer monitoring and water, air and sediment sampling. To well carry out these tasks, some general functions are required like remote operation, video and images capture, scanning and map building, among others. The ECHORD++ innovative proposed solution is carried out in Barcelona as pilot city.
The current need of the City of Barcelona is to mechanize sewer inspections in order to objectify sewer inspections and optimize sewer cleaning expenses of the city. The sewer network of Barcelona is 1,532 km long, from which approximately 50% is accessible, which means that the pipe is at least 1.5 m high and workers are allowed to go inside it. In order to determine the state of the network, visual inspections are done with different frequencies depending on the slope and other characteristics of the sewer. Workers walk all along the pipe, in some sections even four times a year, and decide where it is necessary to clean. Moreover, sewers are classified as confined spaces which require special health and safety measures, in addition to other risks like slippery sections, obstacles or biological risks from the eventual contact with wastewater.
These features made the process of sewer inspection a risky and expensive process that requires improvements urgently. Sewer inspection is a service included in the public management of the sewers of Barcelona. Nowadays, sewer inspections are done by people performing visual inspections and collecting information about the state of the sewage like sediment level and type, pipe obstructions, etc. In this paper the technological proposed solution (a semi-autonomous green robotic solution) is explained. The requirements for the new technology are given by the inherent sewer characteristics, that is, different ranges of pipe sizes, possible high concentration of, not explosive, but toxic gases as hydrogen sulphide, slippery areas, obstacles, atmosphere with 100% humidity, water temperature at 16 °C, and no telecommunication coverage in the sewer. The ECHORD++ project seeks to facilitate real-time decision making, innovation that makes inspection devices more autonomous, to have more degrees of freedom to move around the network, and the possibility to intensify the checking of a zone where impairment has been detected. This technological solution will fulfill environmental legislation and policies.
The present paper describes a vision-based simultaneous localization and mapping system to be applied to Unmanned Aerial Vehicles (UAVs). The main contribution of this work is to propose a novel estimator relying on an Extended Kalman Filter. The estimator is designed in order to fuse the measurements obtained from: (i) an orientation sensor (AHRS); (ii) a position sensor (GPS); and (iii) a monocular camera. The estimated state consists of the full state of the vehicle: position and orientation and their first derivatives, as well as the location of the landmarks observed by the camera. The position sensor will be used only during the initialization period in order to recover the metric scale of the world. Afterwards, the estimated map of landmarks will be used to perform a fully vision-based navigation when the position sensor is not available. Experimental results obtained with simulations and real data show the benefits of the inclusion of camera measurements into the system. In this sense the estimation of the trajectory of the vehicle is considerably improved, compared with the estimates obtained using only the measurements from the position sensor, which are commonly low-rated and highly noisy.
Martinez, H.; Gamiz, J.; Bolea, Y.; Grau, A. International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering Vol. 10, num. 3, p. 354-358 Data de publicació: 2016-03 Article en revista
A new approach to the monocular simultaneous localization and mapping (SLAM) problem is presented in this work. Data obtained from additional bearing-only sensors deployed as wearable devices is fully fused into an Extended Kalman Filter (EKF). The wearable device is introduced in the context of a collaborative task within a human-robot interaction (HRI) paradigm, including the SLAM problem. Thus, based on the delayed inverse-depth feature initialization (DI-D) SLAM, data from the camera deployed on the human, capturing his/her field of view, is used to enhance the depth estimation of the robotic monocular sensor which maps and locates the device. The occurrence of overlapping between the views of both cameras is predicted through geometrical modelling, activating a pseudo-stereo methodology which allows to instantly measure the depth by stochastic triangulation of matched points found through SIFT/SURF. Experimental validation is provided through results from experiments, where real data is captured as synchronized sequences of video and other data (relative pose of secondary camera) and processed off-line. The sequences capture indoor trajectories representing the main challenges for a monocular SLAM approach, namely, singular trajectories and close turns with high angular velocities with respect to linear velocities.
Los robots móviles que trabajan en entornos cerrados, en los que el uso del sistema de navegación GPS no es operativo, usan diferentes tipos de sensores para determinar su posición. No obstante, es significativa la poca utilización de los sensores de señales de audiofrecuencia si la comparamos con el grado de utilización de otros tipos de sensores. La audición presenta varias propiedades muy interesantes, y un robot que posea la capacidad de procesar señales acústicas puede obtener importantes ventajas. El objetivo principal de esta tesis es el de proponer e investigar modelos acústicos y sistemas de localización basados en el tratamiento de señales de audio y concebidos para la autolocalización de robots móviles que trabajen en entornos cerrados, que ayuden a cubrir el vacío existente en este campo. En el desarrollo de la tesis se realiza también una primera aproximación experimental de los sistemas de autolocalización basados en los modelos propuestos con objeto de comprobar su validez mediante la realización de diversos ensayos. En este trabajo se proponen nuevos modelos que contemplan diversas hipótesis simplificativas y que están concebidos especialmente para su aplicación en los sistemas de localización: un modelo teórico, basado en la descripción física de la propagación del sonido, que permite la autolocalización del robot mediante un sistema que se basa en la determinación del módulo de las ganancias de las diferentes funciones de transferencia obtenidas en las distintas posiciones del robot en el recinto, y unos modelos de identificación paramétricos, que permiten la autolocalización del robot mediante un sistema que se basa en el estudio de la variación de los parámetros de los modelos en las distintas posiciones del robot y la posterior aplicación de una función de transformación. En el trabajo realizado también se propone un sistema de filtrado de las señales de audio, situado alrededor de la frecuencia de Schroeder, que permite reducir la complejidad de los modelos propuestos, y se propone también un tratamiento de la incertidumbre de los modelos, en base a la información suministrada por diferentes señales captadas en un número reducido de muestras etiquetadas en el recinto de trabajo del robot, que permite contemplar la posibilidad de su posible utilización en técnicas de SLAM. La validez de los sistemas de localización desarrollados se comprueba con la realización de unos primeros ensayos experimentales, en los que se realiza un estudio comparativo entre ellos y se estudian los puntos fuertes y los puntos débiles de los sistemas de localización presentados. El resultado de este estudio muestra unos resultados bastante similares para los sistemas propuestos, pero pone de manifiesto el menor grado de incertidumbre en los resultados que proporciona el sistema de localización basado en el modelo teórico, respecto a los que presentan los sistemas basados en modelos de identificación paramétricos. Otras conclusiones destacables obtenidas del desarrollo del trabajo de investigación son, además de la comprobación de la viabilidad de los sistemas de localización presentados, la necesidad de determinar el ángulo de orientación del robot en el recinto respecto a algún punto de referencia conocido, debido a la elevada directividad que presenta la onda de presión sonora que se propaga en el interior de los recintos cerrados, o los buenos resultados de las funciones definidas, que permiten obtener, a partir del tratamiento de las características de las distintas señales acústicas captadas por el robot, su posición en el recinto. Otra conclusión importante a destacar deriva de que para la definición del modelo teórico, establecido en base al modelo ondulatorio, se han definido unas expresiones que relacionan la respuesta acústica de los recintos, obtenidas a partir del modelo estadístico de Sabine, con algunos de los parámetros de dicho modelo teórico, facilitando en gran medida su aplicación práctica.
When GPS is not operative in closed environments, mobile robots use different types of sensor in order to locate their position. However, the use of audiofrequency signals sensors is significative lower than other type of sensors. Audio characteristics present interesting properties and robots can obtain great advantages if there are able to process acoustics signals. The main objective of this PhD tesis is to propose and investigate acoustic models and localization systems based in the treatment of audio signals thought for mobile robots self-localization in closed enviroments.This work will help to cover a great gap in this field. In this thesis, a first experimental approach is presented for self-location systems based in proposed models to test their validity by real tests. In this work also new models with simplified hypothesis are proposed which are specially conceived for their application in location systems. First a theoretical model, based in the physical description of sound propagation is proposed, allowing a robot to locate determining the magnitude of gains for different transfer function obtained in different robot location inside an environment. Second, parametrical identification models have been also proposed which allow a robot to locate by means of a system based in the observation of the parameters variations of the models in the different robot locations and the subsequent application of a transformation function. In this research, also an audio signal filtering systems is proposed, near the Schroeder frequency that allow reducing the complexity of the proposed models. The uncertainty of the models is also studied and treated in basis of supplied information by signals acquired in a small set of labeled sampled in the working robot environment that allow the possibility of SLAM techniques usage. The validity of researched location systems is checked with the realization of experimental tests where a comparative study among them is carried out. Strong and weak points in location systems are studied. The outcome of such a study show similar results for proposed systems, but it enhances the lesser degree of uncertainty in the results yielded by the location systems based in the theoretical model than those systems based in parametric identification models. Other relevant conclusions in this research work are, apart from the validation of presented location systems, the need to detemine the orientation angle of the robot respect a known reference point due the high directionality present in the sound pressure wave that is propagated in closed environments. It is also remarkable the excellent results of the proposed functions that allow to obtaining the robot position in a closed environment through the processing of different acoustic signals features acquired by the robot. Another important conclusion to remark for the theoretical model definition is the determination of some mathematical expressions that relate the acoustic response of the environments (obtained from the Sabine's statistical model) with some parameters of such theoretical model making more practicable their application.
Bolea, Y.; Grau, A.; Sanfeliu, A. International Journal of Computer, Electrical, Automation, Control and Information Engineering Vol. 10, num. 6, p. 1020-1023 Data de publicació: 2016 Article en revista