Cooperative Virtual Sensor for Fault Detection and Identification in Multi-UAV Applications

This paper considers the problem of fault detection and identification (FDI) in applications carried out by a group of unmanned aerial vehicles (UAVs) with visual cameras. In many cases, the UAVs have cameras mounted onboard for other applications, and these cameras can be used as bearing-only sensors to estimate the relative orientation of another UAV. The idea is to exploit the redundant information provided by these sensors onboard each of the UAVs to increase safety and reliability, detecting faults on UAV internal sensors that cannot be detected by the UAVs themselves. Fault detection is based on the generation of residuals which compare the expected position of a UAV, considered as target, with the measurements taken by one or more UAVs acting as observers that are tracking the target UAV with their cameras. Depending on the available number of observers and the way they are used, a set of strategies and policies for fault detection are defined. When the target UAV is being visually tracked by two or more observers, it is possible to obtain an estimation of its 3D position that could replace damaged sensors. Accuracy and reliability of this vision-based cooperative virtual sensor (CVS) have been evaluated experimentally in a multivehicle indoor testbed with quadrotors, injecting faults on data to validate the proposed fault detection methods.Comisión Europea H2020 644271Comisión Europea FP7 288082Ministerio de Economia, Industria y Competitividad DPI2015-71524-RMinisterio de Economia, Industria y Competitividad DPI2014-5983-C2-1-RMinisterio de Educación, Cultura y Deporte FP

Cooperative Sensor Fault Recovery in Multi-UAV Systems

IEEE International Conference on Robotics and Automation (ICRA), 16-21 May 2016 Stockholm, SwedenThis paper presents the design and experimental validation of a Fault Detection, Identification and Recovery (FDIR) system intended for multi-UAV applications. The system exploits the information provided by internal position, attitude and visual sensors onboard the UAVs of the fleet for detecting faults in the measurements of the position and attitude sensors of any of the member vehicles. Considering the observations provided by two or more UAVs in a cooperative way, it is possible to identify the source of the fault, but also implement a Cooperative Virtual Sensor (CVS) which provides a redundant position and velocity estimation of the faulty UAV that can be used for replacing its internal sensor. The vision-based FDIR system has been validated experimentally with quadrotors in an indoor testbed. In particular, fault detection and identification has been evaluated injecting a fault pattern offline on the position measurements, while the CVS has been applied in real time for the recovery phase.Ministerio de Educación Cultura y Deporte ICT-2011-28808

MARIT : the design, implementation and trajectory generation with NTG for small UAVs.

This dissertation is about building a Multiple Air Robotics Indoor Testbed (MARIT) for the purpose of developing and validating new methodologies for collaboration and cooperation between heterogeneous Unmanned Air Vehicles (UAVs) as well as expandable to air-and-ground vehicle teams. It introduces a mathematical model for simulation and control of quadrotor Small UAVs (SUAVs). The model is subsequently applied to design an autonomous quadrotor control and tracking system. The dynamics model of quadrotor SUAV is used in several control designs. Each control design is simulated and compared. Based on the comparison, the superior control design is use for experimental flights. Two methods are used to evaluate the control and collect real-time data. The Nonlinear Trajectory Generation (NTG) software package is used to provide optimal trajectories for the SUAVs in MARIT. The dynamics model of the quadrotor is programmed in NTG and various obstacle avoidance scenarios are modeled to establish a platform for optimal trajectory generation for SUAVs. To challenge the capability of NTG for real-time trajectory generation, random obstacles and disturbances are simulated. Various flight simulations validate this trajectory tracking approach

Rapid prototyping flight test environment for autonomous unmanned aerial vehicles

Test facility is essential for most engineering research activities, from modelling and identification to verification of algorithms/methods and final demonstration. It is well known that flight tests for aerospace vehicles are expensive and quite risky. To overcome this, this paper describes a rapid prototyping platform for autonomous unmanned aerial vehicles (UAV) developed at Loughborough University, where a number of unmanned aerial and ground vehicles can perform various flight and other missions under computer control. Flexibility, maintainability and low expenses are assured by a proper choice of vehicles, sensors and system architecture. Among many other technical challenges, precision navigation of the unmanned vehicles and system integrations of commercial-off-the-shelf components from different vendors with different operational environments are discussed in detail. Matlab/Simulink based software development environment provides a seamless rapid prototyping platform from concept and theoretic developments to numerical simulation and finally flight tests. Finally, two scenarios performed by this test facility are presented to illustrate its capability

Design of an embedded microcomputer based mini quadrotor UAV

This paper describes the design and realization of a mini quadrotor UAV (Unmanned Aerial Vehicle) that has been initiated in the Systems and Control Laboratory at the Computer and Automation Research institute of the Hungarian Academy of Science in collaboration with control departments of the Budapest University of Technology and Economics. The mini quadrotor UAV is intended to use in several areas such as camera-based air-surveillance, traffic control, environmental measurements, etc. The paper focuses upon the embedded microcomputer-based implementation of the mini UAV, describes the elements of the implementation, the tools realized for mathematical model building, as well as obtains a brief outline of the control design

Design, Development and Implementation of Intelligent Algorithms to Increase Autonomy of Quadrotor Unmanned Missions

This thesis presents the development and implementation of intelligent algorithms to increase autonomy of unmanned missions for quadrotor type UAVs. A six-degree-of freedom dynamic model of a quadrotor is developed in Matlab/Simulink in order to support the design of control algorithms previous to real-time implementation. A dynamic inversion based control architecture is developed to minimize nonlinearities and improve robustness when the system is driven outside bounds of nominal design. The design and the implementation of the control laws are described. An immunity-based architecture is introduced for monitoring quadrotor health and its capabilities for detecting abnormal conditions are successfully demonstrated through flight testing. A vision-based navigation scheme is developed to enhance the quadrotor autonomy under GPS denied environments. An optical flow sensor and a laser range finder are used within an Extended Kalman Filter for position estimation and its estimation performance is analyzed by comparing against measurements from a GPS module. Flight testing results are presented where the performances are analyzed, showing a substantial increase of controllability and tracking when the developed algorithms are used under dynamically changing environments. Healthy flights, flights with failures, flight with GPS-denied navigation and post-failure recovery are presented