Accurate Landing of Unmanned Aerial Vehicles Using Ground Pattern Recognition

[EN] Over the last few years, several researchers have been developing protocols and applications in order to autonomously land unmanned aerial vehicles (UAVs). However, most of the proposed protocols rely on expensive equipment or do not satisfy the high precision needs of some UAV applications such as package retrieval and delivery or the compact landing of UAV swarms. Therefore, in this work, a solution for high precision landing based on the use of ArUco markers is presented. In the proposed solution, a UAV equipped with a low-cost camera is able to detect ArUco markers sized 56×56 cm from an altitude of up to 30 m. Once the marker is detected, the UAV changes its flight behavior in order to land on the exact position where the marker is located. The proposal was evaluated and validated using both the ArduSim simulation platform and real UAV flights. The results show an average offset of only 11 cm from the target position, which vastly improves the landing accuracy compared to the traditional GPS-based landing, which typically deviates from the intended target by 1 to 3 m.This work was funded by the Ministerio de Ciencia, Innovación y Universidades, Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad, Proyectos I+D+I 2018 , Spain, under Grant RTI2018-096384-B-I00.Wubben, J.; Fabra Collado, FJ.; Tavares De Araujo Cesariny Calafate, CM.; Krzeszowski, T.; Márquez Barja, JM.; Cano, J.; Manzoni, P. (2019). Accurate Landing of Unmanned Aerial Vehicles Using Ground Pattern Recognition. Electronics. 8(12):1-16. https://doi.org/10.3390/electronics8121532S116812Pan, X., Ma, D., Jin, L., & Jiang, Z. (2008). Vision-Based Approach Angle and Height Estimation for UAV Landing. 2008 Congress on Image and Signal Processing. doi:10.1109/cisp.2008.78Tang, D., Li, F., Shen, N., & Guo, S. (2011). UAV attitude and position estimation for vision-based landing. Proceedings of 2011 International Conference on Electronic & Mechanical Engineering and Information Technology. doi:10.1109/emeit.2011.6023131Gautam, A., Sujit, P. B., & Saripalli, S. (2014). A survey of autonomous landing techniques for UAVs. 2014 International Conference on Unmanned Aircraft Systems (ICUAS). doi:10.1109/icuas.2014.6842377Holybro Pixhawk 4 · PX4 v1.9.0 User Guidehttps://docs.px4.io/v1.9.0/en/flight_controller/pixhawk4.htmlGarrido-Jurado, S., Muñoz-Salinas, R., Madrid-Cuevas, F. J., & Medina-Carnicer, R. (2016). Generation of fiducial marker dictionaries using Mixed Integer Linear Programming. Pattern Recognition, 51, 481-491. doi:10.1016/j.patcog.2015.09.023Romero-Ramirez, F. J., Muñoz-Salinas, R., & Medina-Carnicer, R. (2018). Speeded up detection of squared fiducial markers. Image and Vision Computing, 76, 38-47. doi:10.1016/j.imavis.2018.05.004ArUco: Augmented reality library based on OpenCVhttps://sourceforge.net/projects/aruco/Jin, S., Zhang, J., Shen, L., & Li, T. (2016). On-board vision autonomous landing techniques for quadrotor: A survey. 2016 35th Chinese Control Conference (CCC). doi:10.1109/chicc.2016.7554984Chen, X., Phang, S. K., Shan, M., & Chen, B. M. (2016). System integration of a vision-guided UAV for autonomous landing on moving platform. 2016 12th IEEE International Conference on Control and Automation (ICCA). doi:10.1109/icca.2016.7505370Nowak, E., Gupta, K., & Najjaran, H. (2017). Development of a Plug-and-Play Infrared Landing System for Multirotor Unmanned Aerial Vehicles. 2017 14th Conference on Computer and Robot Vision (CRV). doi:10.1109/crv.2017.23Shaker, M., Smith, M. N. R., Yue, S., & Duckett, T. (2010). Vision-Based Landing of a Simulated Unmanned Aerial Vehicle with Fast Reinforcement Learning. 2010 International Conference on Emerging Security Technologies. doi:10.1109/est.2010.14Araar, O., Aouf, N., & Vitanov, I. (2016). Vision Based Autonomous Landing of Multirotor UAV on Moving Platform. Journal of Intelligent & Robotic Systems, 85(2), 369-384. doi:10.1007/s10846-016-0399-zPatruno, C., Nitti, M., Petitti, A., Stella, E., & D’Orazio, T. (2018). A Vision-Based Approach for Unmanned Aerial Vehicle Landing. Journal of Intelligent & Robotic Systems, 95(2), 645-664. doi:10.1007/s10846-018-0933-2Baca, T., Stepan, P., Spurny, V., Hert, D., Penicka, R., Saska, M., … Kumar, V. (2019). Autonomous landing on a moving vehicle with an unmanned aerial vehicle. Journal of Field Robotics, 36(5), 874-891. doi:10.1002/rob.21858De Souza, J. P. C., Marcato, A. L. M., de Aguiar, E. P., Jucá, M. A., & Teixeira, A. M. (2019). Autonomous Landing of UAV Based on Artificial Neural Network Supervised by Fuzzy Logic. Journal of Control, Automation and Electrical Systems, 30(4), 522-531. doi:10.1007/s40313-019-00465-ySITL Simulator (Software in the Loop)http://ardupilot.org/dev/docs/sitl-simulator-software-in-the-loop.htmlFabra, F., Calafate, C. T., Cano, J.-C., & Manzoni, P. (2017). On the impact of inter-UAV communications interference in the 2.4 GHz band. 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC). doi:10.1109/iwcmc.2017.7986413MAVLink Micro Air Vehicle Communication Protocolhttp://qgroundcontrol.org/mavlink/startFabra, F., Calafate, C. T., Cano, J. C., & Manzoni, P. (2018). ArduSim: Accurate and real-time multicopter simulation. Simulation Modelling Practice and Theory, 87, 170-190. doi:10.1016/j.simpat.2018.06.009Careem, M. A. A., Gomez, J., Saha, D., & Dutta, A. (2019). HiPER-V: A High Precision Radio Frequency Vehicle for Aerial Measurements. 2019 16th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON). doi:10.1109/sahcn.2019.882490

An AI-in-Loop Fuzzy-Control Technique for UAV’s Stabilization and Landing

In this paper, an adaptable fuzzy control mechanism for an Unmanned Aerial Vehicle (UAV) to manipulate its mechanical actuators is provided. The mission (landing) for the UAV is defined to track (land on) an object that is detected by a deep learning object detection algorithm. The inputs of the controller are the location and speed of the UAV that have been calculated based on the location of the detected object. Two separate fuzzy controllers are proposed to control the UAV’s motor throttle and its roll and pitch over the mission and landing time. Fuzzy logic controller (FLC) is an intelligent controller that can be used to compensate for the non-linearity behaviour of the UAV by designing a specific fuzzy rule base. These rules will be utilized to adjust the control parameters during the mission and landing period in runtime. To add the effect of the ground for tuning the FLC membership function over the landing operation, a computational flow dynamic (CFD) modeling has been investigated. The proposed techniques is evaluated on MATLAB/Simulink simulation platform and real environment. Statistical analysis of the UAV location reported during stabilization and landing process, on both simulation and real platform, show that the proposed technique outperforms the similar state-of-art control techniques for both mission and landing control.</p

Autonomous, Long-Range, Sensor Emplacement Using Unmanned Aircraft Systems

Automated, in-ground sensor emplacement can significantly improve remote, terrestrial, data collection capabilities. Utilizing a multicopter, unmanned aircraft system (UAS) for this purpose allows sensor insertion with minimal disturbance to the target site or surrounding area. However, developing an emplacement mechanism for a small multicopter, autonomy to manage the target selection and implantation process, as well as long-range deployment are challenging to address. We have developed an autonomous, multicopter UAS that can implant subsurface sensor devices. We enhanced the UAS autopilot with autonomy for target and landing zone selection, as well as ensuring the sensor is implanted properly in the ground. The multicopter UAS, limited by onboard energy, can be carried by a transport aircraft to within 1 km of the desired sensor location site and deployed by a novel parachuting-canister system. Through a comprehensive set of field trials and testing, we assess the effectiveness of each subsystem. We evaluate our system on missions covering distances up to 25 km away in mountains 1 km above the takeoff location

Design of a Specialized UAV Platform for the Discharge of a Fire Extinguishing Capsule

Tato práce se zabývá návrhem systému specializovaného pro autonomní detekci a lokalizaci požárů z palubních senzorů bezpilotních helikoptér. Hašení požárů je zajištěno automatickým vystřelením ampule s hasící kapalinou do zdroje požáru z palubního vystřelovače. Hlavní část této práce se soustředí na detekci požárů v datech termální kamery a jejich následnou lokalizaci ve světě za pomoci palubní hloubkové kamery. Bezpilotní helikoptéra je poté optimálně navigována na pozici pro zajištění průletu ampule s hasící kapalinou do zdroje požáru. Vyvinuté metody jsou detailně analyzovány a jejich chování je testováno jak v simulaci, tak současně i při reálných experimentech. Kvalitativní a kvantitativní analýza ukazuje na použitelnost a robustnost celého systému.This thesis deals with the design of an unmanned multirotor aircraft system specialized for autonomous detection and localization of fires from onboard sensors, and the task of fast and effective fire extinguishment. The main part of this thesis focuses on the detection of fires in thermal images and their localization in the world using an onboard depth camera. The localized fires are used to optimally position the unmanned aircraft in order to effectively discharge an ampoule filled with a fire extinguishant from an onboard launcher. The developed methods are analyzed in detail and their performance is evaluated in simulation scenarios as well as in real-world experiments. The included quantitative and qualitative analysis verifies the feasibility and robustness of the system

Enabling technologies for precise aerial manufacturing with unmanned aerial vehicles

The construction industry is currently experiencing a revolution with automation techniques such as additive manufacturing and robot-enabled construction. Additive Manufacturing (AM) is a key technology that can o er productivity improvement in the construction industry by means of o -site prefabrication and on-site construction with automated systems. The key bene t is that building elements can be fabricated with less materials and higher design freedom compared to traditional manual methods. O -site prefabrication with AM has been investigated for some time already, but it has limitations in terms of logistical issues of components transportation and due to its lack of design exibility on-site. On-site construction with automated systems, such as static gantry systems and mobile ground robots performing AM tasks, can o er additional bene ts over o -site prefabrication, but it needs further research before it will become practical and economical. Ground-based automated construction systems also have the limitation that they cannot extend the construction envelope beyond their physical size. The solution of using aerial robots to liberate the process from the constrained construction envelope has been suggested, albeit with technological challenges including precision of operation, uncertainty in environmental interaction and energy e ciency. This thesis investigates methods of precise manufacturing with aerial robots. In particular, this work focuses on stabilisation mechanisms and origami-based structural elements that allow aerial robots to operate in challenging environments. An integrated aerial self-aligning delta manipulator has been utilised to increase the positioning accuracy of the aerial robots, and a Material Extrusion (ME) process has been developed for Aerial Additive Manufacturing (AAM). A 28-layer tower has been additively manufactured by aerial robots to demonstrate the feasibility of AAM. Rotorigami and a bioinspired landing mechanism demonstrate their abilities to overcome uncertainty in environmental interaction with impact protection capabilities and improved robustness for UAV. Design principles using tensile anchoring methods have been explored, enabling low-power operation and explores possibility of low-power aerial stabilisation. The results demonstrate that precise aerial manufacturing needs to consider not only just the robotic aspects, such as ight control algorithms and mechatronics, but also material behaviour and environmental interaction as factors for its success.Open Acces

Flight coordination solutions for multirotor unmanned aerial vehicles

[EN] As the popularity and the number of Unmanned Aerial Vehicles (UAVs) increases, new protocols are needed to coordinate them when flying without direct human control, and to avoid that these UAVs collide with each other. Testing such novel protocols on real UAVs is a complex procedure that requires investing much time, money and research efforts. Hence, it becomes necessary to first test the developed solutions using simulation. Unfortunately, existing tools present significant limitations: some of them only simulate accurately the flight behavior of a single UAV, while some other simulators can manage several UAVs simultaneously, but not in real time, thus losing accuracy regarding the mobility pattern of the UAV. In this work we address such problem by introducing Arducopter Simulator (ArduSim), a novel simulation platform that allows controlling in soft real-time the flight and communications of multiple UAVs, being the developed protocols directly portable to real devices. Moreover, ArduSim includes a realistic model for the WiFi communications link between UAVs, which was proposed based on real experiments. The chances that two UAVs get close to each other during their flights is increasing as more and more of them populate our skies, causing concerns regarding potential collisions. Therefore, this thesis also proposes the Mission Based Collision Avoidance Protocol (MBCAP), a novel UAV collision avoidance protocol applicable to all types of multicopters flying autonomously. It relies on wireless communications in order to detect nearby UAVs, and to negotiate the procedure to avoid any potential collision. Experimental and simulation results demonstrate the validity and effectiveness of the proposed solution, which typically introduces a small overhead in the range of 15 to 42 seconds for each risky situation successfully handled. The previous solution aims at UAVs performing independent flights, but they can also form a swarm, where more constraints have to be met to avoid collisions among them, and to allow them to complete their task efficiently. Deploying an UAV swarm instead of a single UAV can provide additional benefits when, for example, cargo carrying requirements exceed the lifting power of a single UAV, or when the deployment of several UAVs simultaneously can accelerate the accomplishment of the mission, and broaden the covered area. To this aim, in this work we present the Mission-based UAV Swarm Coordination Protocol (MUSCOP), a solution that allows multiple UAVs to perfectly coordinate their flight when performing planned missions. Experimental results show that the proposed protocol is able to achieve a high degree of swarm cohesion independently of the flight formation adopted, and even in the presence of very lossy channels, achieving minimal synchronization delays and very low position offsets with regard to the ideal case. Currently, there are some other scenarios, such as search and rescue operations, where the deployment of manually guided swarms of UAVs can be necessary. In such cases, the pilot's commands are unknown a priori (unpredictable), meaning that the UAVs must respond in near real-time to the movements of the leader UAV in order to maintain swarm consistency. Hence, in this thesis we also propose the FollowMe protocol for the coordination of UAVs in a swarm where the swarm leader is controlled by a real pilot, and the other UAVs must follow it in real-time to maintain swarm cohesion. Simulation results show the validity of the proposed swarm coordination protocol, detailing the responsiveness limits of our solution, and finding the minimum distances between UAVs to avoid collisions.[ES] A medida que la popularidad de los Vehículos Aéreos No Tripulados (VANTs) se incrementa, también se hacen necesarios nuevos protocolos para coordinarlos en vuelos sin control humano directo, y para evitar que colisionen entre sí. Probar estos nuevos protocolos en VANTs reales es un proceso complejo que requiere invertir mucho tiempo, dinero y esfuerzo investigador. Por lo tanto, es necesario probar en simulación las soluciones previamente implementadas. Lamentablemente, las herramientas actuales tienen importantes limitaciones: algunas simulan con precisión el vuelo de un único VANT, mientras que otros simuladores pueden gestionar varios VANTs simultáneamente aunque no en tiempo real, perdiendo por lo tanto precisión en el patrón de movilidad del VANT. En este trabajo abordamos este problema introduciendo Arducopter Simulator (ArduSim), una nueva plataforma de simulación que permite controlar en tiempo real el vuelo y la comunicación entre múltiples VANTs, permitiendo llevar los protocolos desarrollados a dispositivos reales con facilidad. Además, ArduSim incluye un modelo realista de un enlace de comunicaciones WiFi entre VANTs, el cual está basado en el resultado obtenido de experimentos con VANTs reales. La posibilidad de que dos VANTs se aproximen entre sí durante el vuelo se incrementa a medida que hay más aeronaves de este tipo surcando los cielos, introduciendo peligro por posibles colisiones. Por ello, esta tesis propone Mission Based Collision Avoidance Protocol (MBCAP), un nuevo protocolo de evitación de colisiones para VANTs aplicable a todo tipo de multicópteros mientras vuelan autónomamente. MBCAP utiliza comunicaciones inalámbricas para detectar VANTs cercanos y para negociar el proceso de evitación de la colisión. Los resultados de simulaciones y experimentos reales demuestran la validez y efectividad de la solución propuesta, que introduce un pequeño aumento del tiempo de vuelo de entre 15 y 42 segundos por cada situación de riesgo correctamente resuelta. La solución anterior está orientada a VANTs que realizan vuelos independientes, pero también pueden formar un enjambre, donde hay que cumplir más restricciones para evitar que colisionen entre sí, y para que completen la tarea de forma eficiente. Desplegar un enjambre de VANTs en vez de uno solo proporciona beneficios adicionales cuando, por ejemplo, la necesidad de carga excede la capacidad de elevación de un único VANT, o cuando al desplegar varios VANTs simultáneamente se acelera la misión y se cubre un área mayor. Con esta finalidad, en este trabajo presentamos el protocolo Mission-based UAV Swarm Coordination Protocol (MUSCOP), una solución que permite a varios VANTs coordinar perfectamente el vuelo mientras realizan misiones planificadas. Los resultados experimentales muestran que el protocolo propuesto permite al enjambre alcanzar un grado de cohesión elevado independientemente de la formación de vuelo adoptada, e incluso en presencia de un canal de comunicación con muchas pérdidas, consiguiendo retardos en la sincronización insignificantes y desfases mínimos en la posición con respecto al caso ideal. Actualmente hay otros escenarios, como las operaciones de búsqueda y rescate, donde el despliegue de enjambres de VANTs guiados manualmente puede ser necesario. En estos casos, las órdenes del piloto son desconocidas a priori (impredecibles), lo que significa que los VANTs deben responder prácticamente en tiempo real a los movimientos del VANT líder para mantener la consistencia del enjambre. Por ello, en esta tesis proponemos el protocolo FollowMe para la coordinación de VANTs en un enjambre donde el líder es controlado por un piloto, y el resto de VANTs lo siguen en tiempo real para mantener la cohesión del enjambre. Las simulaciones muestran la validez del protocolo de coordinación de enjambres propuesto, detallando los límites de la solución, y definiendo la distancia mínima entre VANTs para evita[CA] A mesura que la popularitat dels Vehicles Aeris No Tripulats (VANTs) s'incrementa, també es fan necessaris nous protocols per a coordinar-los en vols sense control humà directe, i per a evitar que col·lisionen entre si. Provar aquests nous protocols en VANTs reals és un procés complex que requereix invertir molt de temps, diners i esforç investigador. Per tant, és necessari provar en simulació les solucions prèviament implementades. Lamentablement, les eines actuals tenen importants limitacions: algunes simulen amb precisió el vol d'un únic VANT, mentre que altres simuladors poden gestionar diversos VANTs simultàniament encara que no en temps real, perdent per tant precisió en el patró de mobilitat del VANT. En aquest treball abordem aquest problema introduint Arducopter Simulator (ArduSim), una nova plataforma de simulació que permet controlar en temps real el vol i la comunicació entre múltiples VANTs, permetent portar els protocols desenvolupats a dispositius reals amb facilitat. A més, ArduSim inclou un model realista d'un enllaç de comunicacions WiFi entre VANTs, que està basat en el resultat obtingut d'experiments amb VANTs reals. La possibilitat que dues VANTs s'aproximen entre si durant el vol s'incrementa a mesura que hi ha més aeronaus d'aquest tipus solcant els cels, introduint perill per possibles col·lisions. Per això, aquesta tesi proposa Mission Based Collision Avoidance Protocol (MBCAP), un nou protocol d'evitació de col·lisions per a VANTs aplicable a tota mena de multicòpters mentre volen autònomament. MBCAP utilitza comunicacions sense fils per a detectar VANTs pròxims i per a negociar el procés d'evitació de la col·lisió. Els resultats de simulacions i experiments reals demostren la validesa i efectivitat de la solució proposada, que introdueix un xicotet augment del temps de vol de entre 15 i 42 segons per cada situació de risc correctament resolta. La solució anterior està orientada a VANTs que realitzen vols independents, però també poden formar un eixam, on cal complir més restriccions per a evitar que col·lisionen entre si, i perquè completen la tasca de forma eficient. Desplegar un eixam de VANTs en comptes d'un només proporciona beneficis addicionals quan, per exemple, la necessitat de càrrega excedeix la capacitat d'elevació d'un únic VANT, o quan en desplegar diversos VANTs simultàniament s'accelera la missió i es cobreix una àrea major. Amb aquesta finalitat, en aquest treball presentem el protocol Mission-based UAV Swarm Coordination Protocol (MUSCOP), una solució que permet a diversos VANTs coordinar perfectament el vol mentre realitzen missions planificades. Els resultats experimentals mostren que el protocol proposat permet a l'eixam aconseguir un grau de cohesió elevat independentment de la formació de vol adoptada, i fins i tot en presència d'un canal de comunicació amb moltes pèrdues, aconseguint retards en la sincronització insignificants i desfasaments mínims en la posició respecte al cas ideal. Actualment hi ha altres escenaris, com les operacions de cerca i rescat, on el desplegament d'eixams de VANTs guiats manualment pot ser necessari. En aquests casos, les ordres del pilot són desconegudes a priori (impredictibles), el que significa que els VANTs han de respondre pràcticament en temps real als moviments del VANT líder per a mantindre la consistència de l'eixam. Per això, en aquesta tesi proposem el protocol FollowMe per a la coordinació de VANTs en un eixam on el líder és controlat per un pilot, i la resta de VANTs ho segueixen en temps real per a mantindre la cohesió de l'eixam. Les simulacions mostren la validesa del protocol de coordinació d'eixams proposat, detallant els límits de la solució, i definint la distància mínima entre VANTs per a evitar col·lisions.Fabra Collado, FJ. (2020). Flight coordination solutions for multirotor unmanned aerial vehicles [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/147857TESI

Vision-based Marker-less Landing of a UAS on Moving Ground Vehicle

In recent years the use of unmanned air systems (UAS) has seen extreme growth. These small, often inexpensive platforms have been used to aid in tasks such as search and rescue, medicinal deliveries, disaster relief and more. In many use cases UAS work alongside unmanned ground vehicles (UGVs) to complete autonomous tasks. For end-to-end autonomous cooperation, the UAS needs to be able to autonomously take off and land on the UGV. Current autonomous landing solutions often use fiducial markers to aid in localizing the UGV relative to the UAS, an external ground computer to aid in computation, or gimbaled cameras on-board the UAS. This thesis seeks to demonstrate a vision-based autonomous landing system that does not rely on the use of fiducial markers, completes all computations on-board the UAS, and uses a fixed, non-gimbaled camera. Algorithms are tailored towards low size, weight, and power constraints as all compute and sensing components weigh less than 100 grams. The foundation of this thesis extends upon current efforts by localizing the UGV relative to the UAS using neural network object detection and camera intrinsic properties instead of common place fiducial markers. An object detection neural network is used to detect the UGV within an image captured by the camera on-board the UAS. Then a localization algorithm utilizes the UGV’s pixel position within the image to estimate the UGV’s position relative to the UAS. This estimated position of the UGV will be passed into a command generator that sends setpoints to the on-board PX4 flight control unit (FCU). This autonomous landing system was developed and validated within a high-fidelity simulation environment before conducting outdoor experiments

Brain over Brawn -- Using a Stereo Camera to Detect, Track and Intercept a Faster UAV by Reconstructing Its Trajectory

The work presented in this paper demonstrates our approach to intercepting a faster intruder UAV, inspired by the MBZIRC2020 Challenge 1. By leveraging the knowledge of the shape of the intruder's trajectory we are able to calculate the interception point. Target tracking is based on image processing by a YOLOv3 Tiny convolutional neural network, combined with depth calculation using a gimbal-mounted ZED Mini stereo camera. We use RGB and depth data from ZED Mini to extract the 3D position of the target, for which we devise a histogram-of-depth based processing to reduce noise. Obtained 3D measurements of target's position are used to calculate the position, the orientation and the size of a figure-eight shaped trajectory, which we approximate using lemniscate of Bernoulli. Once the approximation is deemed sufficiently precise, measured by Hausdorff distance between measurements and the approximation, an interception point is calculated to position the intercepting UAV right on the path of the target. The proposed method, which has been significantly improved based on the experience gathered during the MBZIRC competition, has been validated in simulation and through field experiments. The results confirmed that an efficient visual perception module which extracts information related to the motion of the target UAV as a basis for the interception, has been developed. The system is able to track and intercept the target which is 30% faster than the interceptor in majority of simulation experiments. Tests in the unstructured environment yielded 9 out of 12 successful results.Comment: To be published in Field Robotics. UAV-Eagle dataset available at: https://github.com/larics/UAV-Eagl

Design of a quadcopter to work at high temperatures

The project develops the design of a quadcopter to work within industrial plants which can be found even at 80 degrees Celsius. These plants should be checked as a way of detecting faults or cracks to prevent other serious incidents that may arise. Both the whole building as well as industrial machinery, which are inside the plant, should be inspected without the need to wait until the infrastructure is fully cooled down. Both external mechanical defense to get close to surfaces, adapting to customer specifications, as well as mechanical and electronic components in the multicopter are designed. It shall support all the requested temperature at least 80 degrees.El proyecto desarrolla el diseño de un cuadricóptero para trabajar dentro de plantas industriales que se pueden encontrar hasta una temperatura de 80 grados. Estos edificios deben ser revisados continuamente como una forma de detectar fallas o grietas que puedan evitar otros incidentes más graves que pudieran surgir. Todo el edificio, así como la maquinaria industrial que están dentro de la planta, deben ser inspeccionados sin la necesidad de esperar hasta que la infraestructura está totalmente enfriada ...Ingeniería Industria

Effective Target Aware Visual Navigation for UAVs

In this paper we propose an effective vision-based navigation method that allows a multirotor vehicle to simultaneously reach a desired goal pose in the environment while constantly facing a target object or landmark. Standard techniques such as Position-Based Visual Servoing (PBVS) and Image-Based Visual Servoing (IBVS) in some cases (e.g., while the multirotor is performing fast maneuvers) do not allow to constantly maintain the line of sight with a target of interest. Instead, we compute the optimal trajectory by solving a non-linear optimization problem that minimizes the target re-projection error while meeting the UAV's dynamic constraints. The desired trajectory is then tracked by means of a real-time Non-linear Model Predictive Controller (NMPC): this implicitly allows the multirotor to satisfy both the required constraints. We successfully evaluate the proposed approach in many real and simulated experiments, making an exhaustive comparison with a standard approach.Comment: Conference paper at "European Conference on Mobile Robotics" (ECMR) 201