Paulo Jorge Oliveira



Student guidance and supervision




Former post-doc program in ECE at IST


Bruno João Nogueira Guerreiro, with the workplan entitled “Sensor based Control and Localization of Autonomous Vehicles in Unknown Environments”

 Supervisor: Paulo Oliveira             Co-supervisor: Profª. Rita Cunha



The proposed work program builds on the candidate's PhD. thesis contributions to further address several problems related to the control, navigation, and guidance of autonomous vehicles in unknown GPS denied environments. Ultimately, these results will contribute to develop innovative inspection tools for comprehensive inspection procedures, reducing risks and operation costs. There are three fundamental research directions: A. Perception, navigation, and sensor-based simultaneous localization and mapping (SLAM) algorithms with formal observability, convergence, and performance guarantees, considering sensors and strategies that allow for consistent estimation of increasingly unstructured/dynamic environments. B. Sensor-based trajectory tracking control algorithms, considering new sensors, control techniques, and error space formulations, with strong stability and performance results for a wide set of flight regimes and the transitions between them. C. Multi-vehicle and combined sensor-based control and SLAM algorithms, guiding the vehicles to maintain observability of the environment while guaranteeing the convergence to the desired paths, possibly, within a formation of multiple vehicles.


Joint Scientific publications:
RC64], [RC59], [RC47], [RC37], [RC11], [CI171], [CI136], [CI132], [CI117], [CI116], [CI094], [CI059], and [CL04].

FCT Pos-doc scholarship from 1/1/2016 until 31/12/2018.

Current position: Assistant Professor at NOVA University of Lisbon.


              Supervision of PhD Students with the Thesis Completed

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Doctoral Program in Electrical and Computer Engineering, Faculty of Science and Technology, University of Macao

Joel Oliveira, with the workplan entitled “Nonlinear Estimation Techniques for Underwater Navigation and Tracking”



Supervisor: Paulo Oliveira                                 
Co-supervisor: Prof. Carlos Silvestre                                Co-supervisor:   Prof. Pedro Batista



This thesis reports, in the first part, the steps for developing a Portable Navigation Tool for Underwater Scenarios (PONTUS) to be used as a localization device for subsea targets. PONTUS consists of an integrated ultra-short baseline acoustic positioning system aided by an inertial navigation system. The tool’s architecture is fully disclosed, followed by rigorous technical descriptions of the hardware ensemble and software development. A localization technique is then developed to estimate the position of a moving target based on discrete-time direction and biased velocity measurements. A nonlinear system is first designed, followed by a state augmentation that yields an equivalent linear time-varying system. The final estimation solution resorts to a Kalman filter with globally exponentially stable error dynamics. Its performance is assessed via realistic numerical simulations and via a set of experimental results using PONTUS.
    In the second part, four estimators are proposed to tackle the problem of attitude estimation taking into account the rotational motion of the planet. The solutions presented herein put emphasis on the fact that only one vector measurement is explicitly employed in the estimators, which are aided by angular velocity readings collected from a set of triaxial high-grade gyroscopes sensitive to the Earth’s spin. Different strategies, such as explicitly estimating the Earth’s angular velocity or considering time-varying observer gains, are studied aiming at speeding up convergence rates while maintaining high levels of accuracy and low computational complexity. It is further examined the case when both the gyroscope readings and the measurements of the reference vector are corrupted by biases. Realistic simulation tests are detailed that illustrate the performance of all four attitude estimators. In particular, the speed and efficiency of the fastest observers are demonstrated through an extensive set of experimental results.

Keywords: Marine Robotics, Underwater Source Localization, Attitude Estimation, Acoustic Signal Processing, Kalman Filtering, Earth Rotation.

FCT scholarship.

Scientific publications:

[RC81], [RC80], [RC78], [RC72], [RC70],  [RC65], [CI175], [CI150], and [CN13].

Thesis Approved, November 2019. Summary PDF File. Phd Thesis.

Current situation: Post-doc Researcher at FCT, University of Macau.

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Doctoral Program in Electrical and Computer Engineering, IST


Pedro António Duarte Marques Lourenço, with the workplan entitled ‘‘Globally Convergent Simultaneous Localization and Mapping: Design Techniques, Analysis, and Implementation”


Supervisor: Paulo Oliveira                                 
Co-supervisor: Prof. Carlos Silvestre                                Co-supervisor:   Prof. Pedro Batista


Summary of the Thesis (partial):

This dissertation addresses the problem of simultaneous localization and mapping (SLAM), with the main aim of devising strategies to achieve global convergence and stability guarantees, covering its main formulations in terms of the exteroception sensors used. It is argued that, since the pose is unobservable as all the information is relative to the vehicle, removing it from the filter and exploring the relative nature of the measurements is advantageous for that goal. Following that line of reasoning the SLAM problem is divided in two: (i) design an observer for the relative map with global convergence guarantees for its error dynamics; and (ii) find an alternative strategy that allows the computation of the pose from the sensor-based map and the initial pose. Regarding the first part of the problem, this dissertation presents a series of algorithms deeply rooted in a sensor-based approach to the SLAM problem that provide global convergence guarantees. Finally, for the second part of the approach, it is proposed an algorithm that builds on an optimization problem equivalent to the orthogonal Procrustes problem, which has a closed-form solution. Due to the uncertainty present in the sensor-based estimation, the Procrustes problem is also studied thoroughly and a novel uncertainty characterization of its results is presented and validated through extensive Monte Carlo simulations. Simulation and experimental results that complement those of the first part and are included to illustrate the performance of the complete algorithm comprising the Earth-fixed Trajectory and Map estimation in cascade with each of the sensor-based SLAM filters under realistic conditions.


[RC74], [RC68], [RC64], [RC59], [RC53], [CI164], [CI160], [CI159], [CI145], [CI141], [CI136], and [CI132], and [CL04].

FCT scholarship.

Thesis approved with Muito Bom com Distinção e Louvor (top rank), January 2019, PDF File.

Current situation: GMV Aerospace and Defence.


Doctoral Program in Electrical and Computer Engineering, IST


Daniel Luís Laurens Viegas, with the thesis entitled Distributed State Estimation for Multiple Autonomous Vehicles”

Supervisor: Paulo Oliveira                                  Co-supervisor: Prof. Carlos Silvestre                                                    Co-supervisor:  Prof. Pedro Batista


Abstract of the thesis (partial):

This thesis addresses problems on the subject of distributed state estimation for multiple vehicles. In the scenarios that are envisioned, each vehicle must rely on measurements provided by sensors mounted on-board and limited communication with other vehicles to estimate relevant variables such as its own inertial position and linear velocity. For the case in which the vehicles have access to relative position measurements, the proposed distributed state observer features globally exponential stable estimation error dynamics with performance guarantees in the presence of noise in the measurements, and is able to cope with issues such as cycles in the measurement graph and time-varying measurement topologies. Regarding the case in which the vehicles have access to range measurements, conditions for global observability of the nonlinear dynamics of the problem are derived, and the proposed distributed state observer features error dynamics that converge exponentially fast to zero for any initial condition for acyclic measurement topologies. Simulation results for the practical application of a formation of Autonomous Underwater Vehicles (AUVs) working cooperatively are detailed for both cases to validate the theoretical results.

Keywords: Distributed state estimation, Cooperative navigation, Autonomous vehicles, Kalman filtering, State observers.

Prémio da Sociedade Portuguesa de Robótica para a Melhor Tese de Mestrado Nacional em Robótica de 2010, para o Eng. Daniel Viegas, de que fui orientador no Mestrado em Engenharia Eletrotécnica e de Computadores do IST, abril de 2011.

FCT scholarship.

Thesis approved with Muito Bom com Distinção e Louvor (top rank), June 2017,  Ficheiro PDF.

Scientific publications:

[RC69], [RC60], [RC55], [RC51], [RC40], [RC32], [CI154], [CI144], [CI133], [CI114], [CI112], [CI105] e [CI097].


PhD scholarship from FCT. Researcher at the Faculty of Science and Technology, Univ. Macao.

Portuguese Society of Robotics Award for the Best MSc Thesis in Robotics 2010, April 2011.

Current situation: Data Scientist at Feedzai, Lisbon.


Doctoral Program in Electrical and Computer Engineering, IST


Sérgio Daniel Gonçalves Gante Brás, with the thesis entitled Deterministic Position and Attitude Estimation Methods


Supervisor: Prof. Carlos Silvestre                 Co-supervisor: Paulo Oliveira



This thesis proposes new deterministic attitude estimation methods for autonomous platforms. The devised solutions are based on nonlinear observers and on the set-valued observers (SVOs) methodology. Two nonlinear observers are developed for indoor scenarios. The first observer fuses inertial information with measurements from an active vision system. Furthermore, a pan and tilt controller is proposed such that the visual features are kept in the camera’s field of view. The second observer is based on range measurements that are retrieved from acoustic sensors fixed in the moving body reference frame to an array of beacons installed in the inertial frame. Both solutions are validated resorting to experimental prototypes and a high-accuracy motion rate table, which provide ground truth data. Under the framework of SVOs, a different solution for the problem of attitude estimation is proposed, which provides a bounding set, which contains the true rotational state. The sensor readings are assumed corrupted by unknown bounded measurement noise and constant gyro bias. A set containing the rate gyro bias is also obtained and used to reduce the uncertainty of the estimates. Sufficient conditions for boundedness of the estimated set for the cases of multi- and single- vector observations are established. Additionally, two fault detection and isolation (FDI) methods based on bounding sets are proposed for navigation systems equipped with sensors providing inertial measurements and vector observations.

Keywords: Inertial Navigation Systems, Position and Attitude Estimation, Fault Detection and Identification, Nonlinear Observers, Set-valued Observers.

Thesis approved with Muito Bom com Distinção e Louvor (top rank), November 2015,  Ficheiro PDF.

Scientific publications:

[RC67], [RC61], [RC49], [RC39], [RC34], [RC22], [CI146], [CI127], [CI126], [CI113],  [CI110],  [CI104], [CI089], [CI084] e [CI077].


Second Best Student in Electrical and Computer Engineering UTL/Santander Totta awards in 2009.

FCT scholarship.

Current occupation: Atitude and Orbirt Control System Performance Engineer at European Space Agency, Netherlands.

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Doctoral Program in ECE, IST

Tiago Filipe Pires Gaspar with the thesis entitled ‘‘Monocular 3D Positioning and Tracking Systems”


Supervisor: Paulo Oliveira


Abstract (partial):

This thesis addresses the 3D positioning and tracking problem, with special emphasis on indoor applications. This problem consists in estimating the state (composed of the 3D position, velocity, and sometimes acceleration) of a target, typically a person or a moving object, using remote measurements provided by one or more sensors, at fixed locations or at moving platforms. In this case, a new positioning and tracking architecture that solves this problem using measurements provided by a single static pan and tilt camera is proposed. A dynamical model for the target that depends on its angular speed is considered, and the state of the target is computed using a suboptimal stochastic multiple-model estimator. Depth from focus strategies are modified to estimate the distance between a target with unknown dimensions and the camera. This allows us to get rid of the first assumption. The synthesis, design, and analysis, of a novel model based H2 adaptive filter, with convergence guarantees, are also presented. The use of this filter allows us to drop the second assumption. Two new filters that estimate the state of a marine mammal that moves at the sea surface and that is recorded with a camera installed on an Unmanned Aerial Vehicle (UAV) are also proposed. Finally, a strategy that synchronizes video sequences acquired by independently moving cameras that see (possibly) different parts of a common rigidly moving object is also presented. This strategy paves the way for a future extension of the proposed monocular methods to multicamera configurations.

Keywords: Indoor Positioning and Tracking, Nonlinear Filters, Kalman Filters, Complementary Filters, Linear Parameter Varying Observers, Adaptive Estimation, Parameter Identification, Multiple Model Adaptive Estimation.

Thesis approved with Muito Bom com Distinção e Louvor (top rank), July 2015. Presentation:Ficheiro PDF.  Apresentação Ficheiro PDF.

Portuguese Society of Robotics Award for Best PhD Thesis in Robotics 2015, 2016.

Scientific publications:

[RC62], [RC50], [RC42], [RC20], [CI153], [CI131], [CI109], [CI103], [CI095], [CI093], [CI081], [CI76] e [CI071].

FCT scholarship.

Current occupation: Computer Vision Engineer at Reverse Engineering, Lisbon.

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Doctoral Program in Electrical and Computer Engineering, IST

Pinar Oguz Ekim, with the thesis entitled ‘‘Simultaneous Localization and Tracking in Sensor Networks, in the presence of Mobile Robotic Platforms”


Supervisor: Prof. João Pedro Gomes                          Co-supervisor: Paulo Oliveira


Abstract (partial):

This thesis proposes several robust localization algorithms in WSN with a special focus on Target Tracking. The first part of the thesis considers the problem of locating a single source from noisy range measurements of a set of nodes in a WSN. Several techniques are presented for two noise distributions, namely Gaussian and Laplacian, in different space dimensions. Moreover, algorithms based on l1-norm are used to address the Laplacian noise case, which models the presence of outliers in some practical ranging systems that adversely affect the performance of localization algorithms designed for Gaussian noise. The second part of the thesis presents Simultaneous Localization and Tracking in WSN, which aims to determine the positions of sensor nodes and a moving target in a network, given incomplete and inaccurate range measurements between the target and each of the sensors. A modified Euclidean Distance Matrix (EDM) completion problem is solved for a block of target range measurements to approximately set up initial sensor/target positions, and the likelihood function is then iteratively refined through Majorization-Minimization. Simulation results and real indoor experiments show that the proposed algorithms significantly outperform state of the art methods in the presence of outliers as well as Gaussian noise. Additionally, they attain the Cramer Rao Lower Bound for small noise in the Gaussian case. The third part of the thesis addresses sensor network localization problems with additional difficulties.

Keywords: Source localization, sensor network localization, simultaneous localization and tracking, no convex and no smooth minimization, semidefinite programming, maximum likelihood estimation, Laplacian noise, central processing.

Thesis approved with Muito Bom com Distinção e Louvor (top rank), September 2013, PDF File.  Presentation PDF File.


2012 IBM Scientific Award for the work entitled ‘‘Algoritmos robustos localização em redes de sensores com aplicações a seguimento de alvos,” (in Portuguese) May 2013.

FCT scholarship.

Scientific publications:

[RC45], [RC27], [CI138],  [CI129], [CI122], [CI085] e [CI079].


Current occupation: Assistant Professor at İzmir Ekonomi Üniversitesi, Turkey.

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Doctoral Program in Electrical and Computer Engineering, IST

Marco Martins Morgado, with the thesis entitled
‘‘Advanced Ultra-Short Baseline Inertial Navigation Systems”

Supervisor: Paulo Oliveira            Co-supervisor: Prof. Carlos Silvestre


This thesis addresses the synthesis, design, and analysis of modern navigation systems with application to underwater vehicles, focusing on small arrays of acoustic receivers as the main sensor suite installed on-board the underwater vehicle. Novel ultra-short baseline (USBL) tightly-coupled and integrated filtering solutions are proposed to enhance error estimation in strap-down inertial navigation systems (INSs). The improvements of a new tightly-coupled filter, that estimates the INS navigation errors and sensors bias calibration uncertainties, are evidenced when compared to a more conventional loosely- coupled solution, while also being shown to operate closer to state-of-the-art theoretical performance lower bounds. A new approach to the design of globally asymptotically stable (GAS) position and velocity filters, is also presented based directly on the nonlinear ranges readings of the USBL acoustic array. A novel attitude filtering solution is also presented for an intervention underwater vehicle working in tandem with an autonomous surface craft. The design, development, and testing of an integrated USBL and INS to be used as a low-cost navigation system for underwater robotic vehicles is also presented. Experimental results obtained at sea are analyzed and discussed to assess the performance and feasibility of the navigation system.

Keywords: INS, underwater acoustic positioning, USBL, marine robotic vehicles, autonomous underwater vehicle (AUV), position and attitude estimation, Kalman filters, nonlinear observers, underwater acoustic signal generation, matched filters.

Thesis approved with Muito Bom com Distinção e Louvor (top rank), December 2011, PDF File. Presentation PDF File.

Portuguese Society of Robotics Award for the Best PhD Thesis in Robotics 2011, April 2012. PDF File.

Best student paper award for the paper: Morgado M., Oliveira P., and Silvestre C., ‘‘Posterior Cramér-Rao bounds analysis for INS/USBL navigation systems,” 8th IFAC Conference on Manoeuvring and Control of Marine Craft–MCMC 2009, Guarujá, Brasil, September 2009. Best student paper award.

Scientific publications:

[RC65], [RC36], [RC35], [RC31], [RC28], [CI139], [CI120], [CI108], [CI107], [CI101], [CI092], [CI091], [CI086], [CI080], [CI062], [CI054], [CI048], [CI045], and [CN09].

Atualmente: Diretor Geral do Gigajoule Group, Moçambique.

Description: Macintosh HD:Users:PauloOliveira:Desktop:AGREG:CV:index_files:pedrobatista.png Doctoral Program in Electrical and Computer Engineering, IST

 Pedro Tiago Martins Batista, with the thesis entitled ‘‘Sensor-based Navigation and Control of Autonomous Vehicles”

Supervisor: Prof. Carlos Silvestre              Co-supervisor: Paulo Oliveira


This thesis addresses the problems of sensor-based navigation and control of autonomous vehicles. Due to the broad range of topics present in the thesis, the contributions are organized in three main categories, which share the sensor-based concept as a common ground. The first part of the thesis, entitled Sensor-based Linear Motion Estimation, is devoted to estimation of linear motion quantities (position, linear velocities, and linear accelerations), in 3-D, of autonomous vehicles. Novel sensor-based navigation solutions are derived based on different sensors, in particular, position sensors, both in body-fixed and inertial coordinates, single range measurements, and multiple range measurements. The second part of the thesis, entitled Sensor-based Angular Motion Estimation, concerns the estimation of the attitude of a vehicle. A novel sensor-based general framework is devised and exploited in different mobile platforms. The third part of the thesis, entitled Sensor-based Control of Autonomous Underwater Vehicles (AUVs), presents novel sensor-based integrated guidance and control strategies for homing of AUVs to a base station based on an Ultra-short Baseline position sensor. The solutions proposed in the thesis are strongly rooted in well-known control and filtering system theories, and are deeply focused on asymptotic stability properties and achieved performances.

Keywords: autonomous vehicles; sensor-based navigation; sensor-based control; linear motion estimation; attitude estimation; homing.

Thesis approved unanimously (top rank), June 2010, Ficheiro PDF.

Portuguese Society of Robotics Award for the Best PhD Thesis in Robotics 2010, April 2011.

Best session presentation in the 2009 American Control Conference, Saint Louis, USA, June 2009.

FCT scholarship.

Scientific publications:

[RC78], [RC74], [RC73], [RC72], [RC70], [RC69], [RC68], [RC66], [RC65], [RC60], [RC59], [RC55], [RC53], [RC52], [RC51], [RC46], [RC44], [RC41], [RC40], [RC38], [RC37], [RC32], [RC31], [RC30], [RC29], [RC28], [RC26], [RC24], [RC23], [RC19], [RC18], [RC16], [RC15], [RC14], [RC12], [RC09], [RC08], [CI164], [CI163], [CI162],[CI160], [CI159], [CI156], [CI155], [CI154], [CI152], [CI150], [CI147], [CI145], [CI144], [CI143], [CI142], [CI141], [CI136], [CI135], [CI134], [CI133], [CI130], [CI125], [CI124], [CI120], [CI119], [CI117], [CI116], [CI115], [CI114], [CI113], [CI112], [CI111], [CI105], [CI101], [CI100], [CI099], [CI097], [CI092], [CI090], [CI088], [CI087], [CI082], [CI075], [CI074], [CI073], [CI072], [CI068], [CI058], [CI052], [CI049], [CI043] e [CN07].

Current occupation: Assistant Professor at SDC/DEEC/IST. 


Doctoral Program in Electrical and Computer Engineering, IST

 José Maria Fernandes Vasconcelos, with the thesis entitled
‘‘Nonlinear Navigation System Design with Application to Autonomous Vehicles”

Supervisor: Prof. Carlos Silvestre           Co-supervisor: Paulo Oliveira


This thesis addresses the design of nonlinear navigation systems for autonomous vehicles, following two main approaches: Kalman filter based estimators, and Lyapunov theory based nonlinear observers. The proposed Kalman filter architectures are designed for accurate position and attitude estimation using low-cost sensor suites. An extended Kalman filter is adopted to merge a high accuracy inertial navigation system with advanced aiding information, namely i) frequency contents of vector measurements, ii) vehicle model dynamics, and iii) LASER range measurements. In alternative, simple yet effective multirate complementary Kalman filters are proposed, endowed with stability and performance properties. The navigation systems are validated using realistic vehicle simulators, and experimental data collected onboard the DELFIMx autonomous surface craft. The second approach addresses the design of nonlinear observers in non-Euclidean spaces. The observers are derived resorting to Lyapunov theory, bearing stability and robustness properties in the presence of inertial sensor non-idealities. The considered sensor readings are provided by an inertial measurement unit and i) landmark measurements, ii) vector observations, and iii) GPS receivers. The regions of attraction are explicitly characterized, and an output feedback configuration is proposed, allowing for the practical implementation of the algorithms.

Keywords: Nonlinear observers, Lyapunov stability theory, Navigation systems, Kalman filters, Complementary filters, Autonomous vehicles.

Honnors in the UTL/Caixa Geral Depósitos Young Researcher Awards, in the field of Computer Engineering, May 2010.

Thesis approved unanimously (top rank), January 2010, 
Ficheiro PDF.  Apresentação: Ficheiro PDF.

Scientific publications:
RC36], [RC34], [RC25], [RC22], [RC21], [RC17], [RC15], [RC13], [RC11], [RC07], [CI104], [CI089], [CI084], [CI083], [CI078], [CI077], [CI072], [CI069], [CI065], [CI064], [CI063], [CI062], [CI059], [CI057], [CI054], [CI053], [CI048], [CI047], [CI045], [CI039] e [CI33].

Current occupation: Project Manager at Altran, Lisbon.

Doctoral Program in Electrical and Computer Engineering, IST

 Alex Alcocer Penas, with the thesis entitled ‘‘Positioning and Navigation Systems for Robotic Underwater Vehicles’’

Supervisor: Paulo Oliveira                     Co-supervisor:Prof. António Pascoal


This thesis addresses the problem of underwater navigation of robotic vehicles using acoustic positioning systems. Several estimation problems are considered that are based on Range-Only measurements obtained from the Times of Arrival of acoustic signals. First, the Range-Only localization problem is addressed, which consists of determining the position of a vehicle given ranges to a set of landmarks with known locations. This problem arises in acoustic positioning systems such as GIB (GPS Intelligent Buoys). Several solutions based on Least Squares, Maximum Likelihood, and Extended Kalman filtering are presented and applied to real experimental data obtained during sea trials. Special attention is given to performance issues and practical problems related to acoustic positioning systems such as sound speed estimation and multipath mitigation. Second, the problem of pose estimation with Range-Only measurements is addressed, in which the vehicle is equipped with an array of beacons with known relative position and uses range measurements to a set of Earth fixed landmarks. A Maximum Likelihood estimator is derived that requires solving a constrained minimization problem on the Special Euclidean group SE(3). Borrowing tools from optimization on Riemannian manifolds, generalized gradient and Newton methods are derived to solve this problem. An alternative solution is derived in a system theoretic setting by adopting a suitable Lyapunov function that is a function of range measurements only, yielding convergence conditions. Finally, the thesis addresses the post-processing of acoustic positioning data. An extension of diffusion-based trajectory observers is derived that incorporates measurement error information.

Keywords: Underwater Navigation, Acoustic Positioning Systems, Range-Only measurements, Localization, Pose estimation, Maximum Likelihood estimation

Thesis approved unanimously (top rank), January 2010, 
Ficheiro PDF.

FCT Scholarship.

Scientific publications:
[RC05], [CI070], [CI066], [CI056], [CI051], [CI050], [CI046], [CI042] e [CI034].

Current occupation: Associate Professor, Electrical Engineering and Robotics @ OsloMet - Oslo Metropolitan University, Norway.


Supervision of PhD Students with the Theses Ongoing


Doctoral Program in Mechanical Engineering, IST

João Pedro Dias Madeiras, with the workprogram entitled “Inspection with Unmanned Aerial Vehicles”



Start date:  January 2021
End date:  December 2024

Supervisor: Paulo Oliveira                                                    Supervisor: Prof. Carlos Cardeira


Summary of the Workplan (in Portuguese):

A scientific research plan is proposed for the development of Advanced Navigation Systems design methodologies with applications to Inspection with Unmanned Aerial Vehicles. For this work, it is foreseen the operation of unmanned, dynamic and high-performance platforms in unstructured environments and with high social impact objectives such as the inspection of infrastructures, the location in relation to conspicuous points in the environment, the surveillance of sensitive areas and tracking uncooperative targets. With strong inspiration and motivation in energy criteria, we intend to use: i) techniques for synthesis of dynamic systems based on recent developments in the theory of Optimization for Linear and Non-Linear Systems, ii) Sensory Fusion to obtain Non-Linear Navigation Systems and iii) non-linear techniques (Lyapunov Theory) or total linearization techniques (Lyapunov Transformations, Polynomial Systems, ...). The obtained solutions will be validated in prototypes existing in IDMEC / LAETA.



Scholarship from FCT from January 2021 until December 2024.


Doctoral Program in Mechanical Engineering, IST

Pedro Miguel Gomes Outeiro, with the workplan entitled “Guidance, Navigation, and Control Systems for Unknown Load Transportation by UAVs”



Start date:  November 2019
End date:  October 2023

Supervisor: Paulo Oliveira                                                    Supervisor: Prof. Carlos Cardeira


Summary of the Workplan:

The development of methodologies for the project of integrated Guidance, Navigation and Control systems with application of Unmmaned Aerial Vehicles is proposed. In this work the use of umanned platforms, dynamic and of high performance in unstructured environments is foreseen. High societal objectives are pursued namely on the transportation and distribution of unknown loads in isolated regions, search and rescue, intervention on the environment, inspection of critical infrastructures, and surveillance of sensitive areas. Inspired on energetic criteria the work will resort to: i) synthesis techniques for linear systems based on recent advances in the Optimization Theory for Linear and Nonlinear Systems; ii) Linear Parametric Varying Systems; iii) Nonlinear Lyapunov techniques or full linearization (feedback linearization or flat systems). The solutions obtained will be validated in prototypes available in the CSI/IDMEC/LAETA.



[RC76], [RC75], [CI178], [CI176], [CI174].

Scholarship from FCT from November 2019 until October 2023.

  Supervision of MSc Students

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Master in Science in Electrical and Computer Engineering, IST
Bruno Miguel Simões Carvalho Cardeira, with the thesis entitled ‘‘Arquiteturas para Navegação Inercial/GPS com Aplicação a Veículos Autónomos” (in Portuguese)

Supervisor: Prof. Carlos Silvestre            Co-supervisor  : Paulo Oliveira


This thesis addresses the development and integration of a strapdown navigation system to determine the position and attitude of unmanned vehicles, using accelerometers, magnetometers and rate gyros triads aided by Global Positioning System (GPS) measurements. The current work resorts to Complementary Filtering techniques to implement the navigation system developed on Earth frame coordinates for the position estimation, with the velocity estimated in the body frame and with the attitude described using Euler angles. Special features include bias estimation and removal in inertial sensors. An attitude-aiding device, referred to as Magneto-Pendular Sensor, is implemented and the synthesis of the multirate complementary filters is outlined. Stability and performance properties of the proposed filters are derived to solve the position and attitude estimation problem. The proposed filters parameters are synthesized based on optimality results, regarding the available sensor suite characteristics, that can be stochastic or frequency based. It is also presented and briefly discussed a nonlinear transformation that finds application in the stability and performance analysis of the position and attitude complementary filters. Formulated in discrete-time, the position and attitude complementary filters allow for practical implementation without requiring high performance signal processing hardware and maintaining all their stability and performance properties. The hardware architecture for the implementation of the real-time navigation system is presented and the different hardware modules are described. Integration issues, both electromagnetic and mechanical, that arise from the interaction of different systems are also addressed. The on-board systems and ground station design made from Commercial-Off-The-Shelf (COTS) sub-systems and custom developed hardware/ software modules are briefly presented. Finally, the overall system performance is evaluated both in simulation and in sea trials using the DELFIMx catamaran developed at the Institute for Systems and Robotics - Lisbon.

Keywords: Inertial Navigation Systems, Complementary Filters, Strapdown Systems, Inertial Sensors, Avionic Systems, And Autonomous Vehicles.

Thesis approved unanimously (top rank), March 2009,  PDF File.

[RC17], [RC16], [RC15], [CI090], [CI088], [CI082] e [CI065].

Current occupation: Centre for Maritime Research and Experimentation,Italy.

versão de 1 de fevereiro de 2016.