Showing papers in "Journal of Intelligent and Robotic Systems in 2014"

Networking Models in Flying Ad-Hoc Networks (FANETs): Concepts and Challenges

Abstract: In recent years, the capabilities and roles of Unmanned Aerial Vehicles (UAVs) have rapidly evolved, and their usage in military and civilian areas is extremely popular as a result of the advances in technology of robotic systems such as processors, sensors, communications, and networking technologies. While this technology is progressing, development and maintenance costs of UAVs are decreasing relatively. The focus is changing from use of one large UAV to use of multiple UAVs, which are integrated into teams that can coordinate to achieve high-level goals. This level of coordination requires new networking models that can be set up on highly mobile nodes such as UAVs in the fleet. Such networking models allow any two nodes to communicate directly if they are in the communication range, or indirectly through a number of relay nodes such as UAVs. Setting up an ad-hoc network between flying UAVs is a challenging issue, and requirements can differ from traditional networks, Mobile Ad-hoc Networks (MANETs) and Vehicular Ad-hoc Networks (VANETs) in terms of node mobility, connectivity, message routing, service quality, application areas, etc. This paper identifies the challenges with using UAVs as relay nodes in an ad-hoc manner, introduces network models of UAVs, and depicts open research issues with analyzing opportunities and future work.

A Practical Multirobot Localization System

Abstract: We present a fast and precise vision-based software intended for multiple robot localization. The core component of the software is a novel and efficient algorithm for black and white pattern detection. The method is robust to variable lighting conditions, achieves sub-pixel precision and its computational complexity is independent of the processed image size. With off-the-shelf computational equipment and low-cost cameras, the core algorithm is able to process hundreds of images per second while tracking hundreds of objects with millimeter precision. In addition, we present the method's mathematical model, which allows to estimate the expected localization precision, area of coverage, and processing speed from the camera's intrinsic parameters and hardware's processing capacity. The correctness of the presented model and performance of the algorithm in real-world conditions is verified in several experiments. Apart from the method description, we also make its source code public at http://purl.org/robotics/whycon ; so, it can be used as an enabling technology for various mobile robotic problems.

Design of a Commercial Hybrid VTOL UAV System

Abstract: For the last four decades Unmanned Air Vehicles (UAVs) have been extensively used for military operations that include tracking, surveillance, active engagement with weapons and airborne data acquisition. UAVs are also in demand commercially due to their advantages in comparison to manned vehicles. These advantages include lower manufacturing and operating costs, flexibility in configuration depending on customer request and not risking the pilot on demanding missions. Even though civilian UAVs currently constitute 3 % of the UAV market, it is estimated that their numbers will reach up to 10 % of the UAV market within the next 5 years. Most of the civilian UAV applications require UAVs that are capable of doing a wide range of different and complementary operations within a composite mission. These operations include taking off and landing from limited runway space, while traversing the operation region in considerable cruise speed for mobile tracking applications. This is in addition to being able traverse in low cruise speeds or being able to hover for stationary measurement and tracking. All of these complementary and but different operational capabilities point to a hybrid unmanned vehicle concept, namely the Vertical Take-Off and Landing (VTOL) UAVs. In addition, the desired UAV system needs to be cost-efficient while providing easy payload conversion for different civilian applications. In this paper, we review the preliminary design process of such a capable civilian UAV system, namely the TURAC VTOL UAV. TURAC UAV is aimed to have both vertical take-off and landing and Conventional Take-off and Landing (CTOL) capability. TURAC interchangeable payload pod and detachable wing (with potential different size variants) provides capability to perform different mission types, including long endurance and high cruise speed operations. In addition, the TURAC concept is to have two different variants. The TURAC A variant is an eco-friendly and low-noise fully electrical platform which includes 2 tilt electric motors in the front, and a fixed electric motor and ducted fan in the rear, where as the TURAC B variant is envisioned to use high energy density fuel cells for extended hovering time. In this paper, we provide the TURAC UAV's iterative design and trade-off studies which also include detailed aerodynamic and structural configuration analysis. For the aerodynamic analysis, an in-house software including graphical user interface has been developed to calculate the aerodynamic forces and moments by using the Vortex Lattice Method (VLM). Computational Fluid Dynamics (CFD) studies are performed to determine the aerodynamic effects for various configurations For structural analysis, a Finite Element Model (FEM) of the TURAC has been prepared and its modal analysis is carried out. Maximum displacements and maximal principal stresses are calculated and used for streamlining a weight efficient fuselage design. Prototypes have been built to show success of the design at both hover and forward flight regime. In this paper, we also provide the flight management and autopilot architecture of the TURAC. The testing of the controller performance has been initiated with the prototype of TURAC. Current work focuses on the building of the full fight test prototype of the TURAC UAV and aerodynamic modeling of the transition flight.

Gaussian-Process-Based Real-Time Ground Segmentation for Autonomous Land Vehicles

Abstract: Ground segmentation is a key component for Autonomous Land Vehicle (ALV) navigation in an outdoor environment. This paper presents a novel algorithm for real-time segmenting three-dimensional scans of various terrains. An individual terrain scan is represented as a circular polar grid map that is divided into a number of segments. A one-dimensional Gaussian Process (GP) regression with a non-stationary covariance function is used to distinguish the ground points or obstacles in each segment. The proposed approach splits a large-scale ground segmentation problem into many simple GP regression problems with lower complexity, and can then get a real-time performance while yielding acceptable ground segmentation results. In order to verify the effectiveness of our approach, experiments have been carried out both on a public dataset and the data collected by our own ALV in different outdoor scenes. Our approach has been compared with two previous ground segmentation techniques. The results show that our approach can get a better trade-off between computational time and accuracy. Thus, it can lead to successive object classification and local path planning in real time. Our approach has been successfully applied to our ALV, which won the championship in the 2011 Chinese Future Challenge in the city of Ordos.

Robust Backstepping Control Based on Integral Sliding Modes for Tracking of Quadrotors

Abstract: Modern non-inertial robots are usually underactuated, such as fix or rotary wing Unmanned Aerial Vehicles (UAVs), underwater or nautical robots, to name a few Those systems are subject to complex aerodynamic or hydrodynamic forces which make the dynamic model more difficult, and typically are subject to bounded smooth time-varying disturbances In these systems, it is preferred a formal control approach whose closed-loop system can predict an acceptable performance since deviations may produce instability and may lead to catastrophic results Backstepping provides an intuitive solution since it solves underactuation iteratively through slaving the actuated subsystem so as to provide a virtual controller in order to stabilize the underactuated subsystem However it requires a full knowledge of the plant and derivatives of the state, which it is prone to instability for any uncertainty; and although robust sliding mode has been proposed, discontinuities may be harmful for air- or water-borne nonlinear plants In this paper, a novel robust backstepping-based controller that induces integral sliding modes is proposed for the Newton---Euler underactuated dynamic model of a quadrotor subject to smooth bounded disturbances, including wind gust and sideslip aerodynamics, as well as dissipative drag in position and orientation dynamics The chattering-free sliding mode compensates for persistent or intermittent, and possible unmatched state dependant disturbances with reduced information of the dynamic model Representative simulations are presented and discussed

A Framework for Using Unmanned Aerial Vehicles for Data Collection in Linear Wireless Sensor Networks

Abstract: The wireless sensor network (WSN) technology have been evolving very quickly in recent years. Sensors are constantly increasing in sensing, processing, storage, and communication capabilities. In many WSNs that are used in environmental, commercial and military applications, the sensors are lined linearly due to the linear nature of the structure or area that is being monitored making a special class of these networks; We defined these in a previous paper as Linear Sensor Networks (LSNs), and provided a classification of the different types of LSNs. A pure multihop approach to route the data all the way along the linear network (e.g. oil, gas and water pipeline monitoring, border monitoring, road-side monitoring, etc.), which can extend for hundreds or even thousands of kilometers can be very costly from an energy dissipation point of view. In order to significantly reduce the energy consumption used in data transmission and extend the network lifetime, we present a framework for monitoring linear infrastructures using LSNs where data collection and transmission is done using Unmanned Aerial Vehicles (UAVs). The system defines four types of nodes, which include: sensor nodes (SNs), relay nodes (RNs), UAVs, and sinks. The SNs use a classic WSN multihop routing approach to transmit their data to the nearest RN, which acts as a cluster head for its surrounding SNs. Then, a UAV moves back and forth along the linear network and transport the data that is collected by the RNs to the sinks located at both ends of the LSN. We name this network architecture a UAV-based LSNs (ULSNs). This approach leads to considerable savings in node energy consumption, due to a significant reduction of the transmission ranges of the SN and RN nodes and the use of a one-hop transmission to communicate the data from the RNs to the UAV. Furthermore, the strategy provides for reduced interference between the RNs that can be caused by hidden terminal and collision problems, that would be expected if a pure multihop approach is used at the RN level. In addition, three different UAV movement approaches are presented, simulated, and analyzed in order to measure system performance under various network conditions.

A Survey and Categorization of Small Low-Cost Unmanned Aerial Vehicle System Identification

Abstract: Remote sensing has traditionally be done with satellites and manned aircraft. While these methods can yield useful scientific data, satellites and manned aircraft have limitations in data frequency, process time, and real time re-tasking. Small low-cost unmanned aerial vehicles (UAVs) can bridge the gap for personal remote sensing for scientific data. Precision aerial imagery and sensor data requires an accurate dynamics model of the vehicle for controller development. One method of developing a dynamics model is system identification (system ID). The purpose of this paper is to provide a survey and categorization of current methods and applications of system ID for small low-cost UAVs. This paper also provides background information on the process of system ID with in-depth discussion on practical implementation for UAVs. This survey divides the summaries of system ID research into five UAV groups: helicopter, fixed-wing, multirotor, flapping-wing, and lighter-than-air. The research literature is tabulated into five corresponding UAV groups for further research.

Intelligent Coverage Path Planning for Agricultural Robots and Autonomous Machines on Three-Dimensional Terrain

Abstract: Field operations should be done in a manner that minimizes time and travels over the field surface. Automated and intelligent path planning can help to find the best coverage path so that costs of various field operations can be minimized. The algorithms for generating an optimized field coverage pattern for a given 2D field has been investigated and reported. However, a great proportion of farms have rolling terrains, which have a considerable influence on the design of coverage paths. Coverage path planning in 3D space has a great potential to further optimize field operations and provide more precise navigation. Supplementary to that, energy consumption models were invoked taking into account terrain inclinations in order to provide the optimal driving direction for traversing the parallel field-work tracks and the optimal sequence for handling these tracks under the criterion of minimizing direct energy requirements. The reduced energy requirements and consequently the reduced emissions of atmospheric pollutants, e.g. CO2 and NO, are of major concern due to their contribution to the greenhouse effect. Based on the results from two case study fields, it was shown that the reduction in the energy requirements when the driving angle is optimized by taking into account the 3D field terrain was 6.5 % as an average for all the examined scenarios compared to the case when the applied driving angle is optimized assuming even field terrain. Additional reduction is achieved when sequence of field tracks is optimized by taking into account inclinations for driving up and down steep hills.

Generation of Bezier Curve-Based Flyable Trajectories for Multi-UAV Systems with Parallel Genetic Algorithm

Abstract: In recent years, Unmanned Aerial Vehicles (UAVs) have been used in many military and civil application areas, due to their increased endurance, performance, portability, and their larger payload-carrying, computing and communication capabilities. Because of UAVs' complex operation areas and complicated constraints related to the assigned task, they have to fly on a path, which is calculated online and/or offline to satisfy these constraints and to check some control points in the operation theatre. If the number of control points and constraints increases, finding a feasible solution takes up too much time in this large operation area. In this case, the use of multi-UAVs decreases operation completion time; however, this usage increases the complexity of finding a feasible path problem. This problem is typically NP-hard and genetic algorithms have been successfully utilized for solving it in the last few decades. This paper presents how a flyable trajectory can be constructed for multi-UAV systems by using a Genetic Algorithm (GA) in a known environment and at a constant altitude. A GA is implemented parallel in a multi-core environment to increase the performance of the system. First, a feasible path is calculated by using a parallel GA, and then the path is smoothed by using Bezier curves to convert it flyable. Preliminary results show that the proposed method provides an effective and feasible path for each UAV in an Unmanned Aerial System with multi-UAVs. The proposed system is realized in Java with a GUI for showing results. This paper also outlines future work that can be conducted on the multi-UAV path planning.

A Survey of Optical Flow Techniques for Robotics Navigation Applications

Abstract: Optical flow has been widely used by insects and birds to support navigation functions. Such information has appealing capabilities for application to ground and aerial robots, especially for navigation and collision avoidance in urban or indoor areas. The purpose of this paper is to provide a survey of existing optical flow techniques for robotics navigation applications. Detailed comparisons are made among different optical-flow-aided navigation solutions with emphasis on the sensor hardware as well as optical flow motion models. A summary of current research status and future research directions are further discussed.

Multiple UAV Formations for Cooperative Source Seeking and Contour Mapping of a Radiative Signal Field

Abstract: In this paper, four scenarios are presented for cooperative source seeking and contour mapping of a radiative signal field by multiple UAV formations. A source seeking strategy is adopted with saturation, and then it is modified to achieve contour mapping of the signal field with the moving source situation considered. A formation controller used for consensus problem is simplified and applied in the scenarios to stabilize the multiple UAV formation flight during source detection. The contour mapping strategy and the formation control algorithm are combined to guarantee stable source seeking and contour mapping in both circular flight path and square flight path via multiple UAV formations.

Spline-Based RRT Path Planner for Non-Holonomic Robots

Abstract: Planning in a cluttered environment under differential constraints is a difficult problem because the planner must satisfy the external constraints that arise from obstacles in the environment and the internal constraints due to the kinematic/dynamic limitations of the robot. This paper proposes a novel Spline-based Rapidly-exploring Random Tree (SRRT) algorithm which treats both the external and internal constraints simultaneously and efficiently. The computationally expensive numerical integration of the system dynamics is replaced by an efficient spline curve parameterization. In addition, the SRRT guarantees continuity of curvature along the path satisfying any upper-bounded curvature constraints. This paper presents the underlying theory to the SRRT algorithm and presents simulation and experiment results of a mobile robot efficiently navigating through cluttered environments.

Evaluation of a Small Socially-Assistive Humanoid Robot in Intelligent Homes for the Care of the Elderly

Abstract: The ageing population phenomenon is pushing the design of innovative solutions to provide assistance to the elderly. In this context a socially---assistive robot can act as a proactive interface in a smart-home environment, providing multimodal communication channels and generating positive feelings in users. The present paper reports results of a short term and a long term evaluation of a small socially assistive humanoid robot in a smart home environment. Eight elderly people tested an integrated smart---home robot system in five real---world scenarios. Six of the participants experienced the system in two sessions over a two week period; the other two participants had a prolonged experience of eight sessions over a three month period. Results showed that the small humanoid robot was trusted by the participants. A cross---cultural comparison showed that results were not due to the cultural background of the participants. The long term evaluation showed that the participants might engage in an emotional relationship with the robot, but that perceived enjoyment might decrease over time.

Active SLAM and Exploration with Particle Filters Using Kullback-Leibler Divergence

Abstract: Autonomous exploration under uncertain robot location requires the robot to use active strategies to trade-off between the contrasting tasks of exploring the unknown scenario and satisfying given constraints on the admissible uncertainty in map estimation. The corresponding problem, namely active SLAM (Simultaneous Localization and Mapping) and exploration, has received a large attention from the robotic community for its relevance in mobile robotics applications. In this work we tackle the problem of active SLAM and exploration with Rao-Blackwellized Particle Filters. We propose an application of Kullback-Leibler divergence for the purpose of evaluating the particle-based SLAM posterior approximation. This metric is then applied in the definition of the expected information from a policy, which allows the robot to autonomously decide between exploration and place revisiting actions (i.e., loop closing). Extensive tests are performed in typical indoor and office environments and on well-known benchmarking scenarios belonging to SLAM literature, with the purpose of comparing the proposed approach with the state-of-the-art techniques and to evaluate the maturity of truly autonomous navigation systems based on particle filtering.

Improving Finite State Impedance Control of Active-Transfemoral Prosthesis Using Dempster-Shafer Based State Transition Rules

Abstract: Finite state impedance (FSI) control is a widely used approach to control active-transfemoral prostheses (ATP). Current design of state transition rules depends on hard thresholding of intrinsic mechanical measurements, which cannot cope well with uncertainty related with intra- and inter-subject variations of these intrinsic recordings. In this study, we aimed to generate more robust FSI control of ATP against these variations by using Dempster-Shafer theory (DST)-based transition rules. The FSI control with DST-based rules was implemented on an instrumented ATP, evaluated on five able-bodied subjects and one patient with a unilateral transfemoral amputation. Then the DSP based transition rules were compared to the control with hard threshold (HT)-based transition rules. The results showed that when compared to the hard thresholding approach, the DST yielded enhanced accuracy in state transition timing and reduced control errors when intra- and inter-subject variations were presented. Additionally, the parameters of DST-based rules were uniform for all the subjects tested, allowing for easy and efficient transition rule design and calibration. The outcome of this study can lead to further improvement of robust, practical, and self-contained ATP design, which in turn will advance the motor function of patients with lower limb amputations.

An Approach Toward Visual Autonomous Ship Board Landing of a VTOL UAV

Abstract: We present the design and implementation of a vision based autonomous landing algorithm using a downward looking camera. To demonstrate the efficacy of our algorithms we emulate the dynamics of the ship-deck, for various sea states and different ships using a six degrees of freedom motion platform. We then present the design and implementation of our robust computer vision system to measure the pose of the shipdeck with respect to the vehicle. A Kalman filter is used in conjunction with our vision system to ensure the robustness of the estimates. We demonstrate the accuracy and robustness of our system to occlusions, variation in intensity, etc. using our testbed.

Hybrid Adaptive Control for Aerial Manipulation

Abstract: This paper presents a control scheme to achieve dynamic stability in a mobile manipulating unmanned aerial vehicle (MM-UAV) using a combination of Gain scheduling and Lyapunov based model reference adaptive control (MRAC). Our test flight results indicate that we can accurately model and control our aerial vehicle when both moving the manipulators and interacting with target objects. Using the Lyapunov stability theory, the controller is proven to be stable. The simulation results showed how the MRAC is capable of stabilizing the oscillations produced from the unstable PI-D attitude control loop. Finally a high level control system based on a switching automaton is proposed in order to ensure the saftey of the aerial manipulation missions.

A Novel Actuation Concept for a Multi Rotor UAV

Abstract: This paper proposes a novel strategy to improve the performance and fault tolerance of multi-rotor vehicles. The proposed strategy uses dual axis tilting propellers and thus enables three different actuation mechanisms, namely, gyroscopic torques, thrust vectoring and differential thrusting. Unlike the conventional quadrotor, the proposed strategy offers a wider range of control torques by combining the three actuation mechanisms. Conventional quadrotors cannot be reconfigured if one of rotors fails. However, the proposed strategy is still able to reconfigure the vehicle with complete failure of one rotor and a pair of adverse motors. In order to prove this concept, a dual axis tilting UAV is first designed and prototyped. Next, a mathematical representation of the prototyped vehicle is modelled and verified using experiments. Then, a control system is developed based on a PD controller and pseudoinverse control allocator and validated through tests on a rig and flight tests. The tests show that the vehicle is faster than a conventional counterpart and that it can resist the failure of two rotors. Finally, this paper suggests how to lead further substantial improvements in performance.

Chattering-Free Sliding Mode Altitude Control for a Quad-Rotor Aircraft: Real-Time Application

Abstract: Nowadays, the chattering problem in sliding mode control is one of the most important points to consider in real-time applications. To address this problem, a real-time robust altitude control scheme is proposed for the efficient performance of a Quad-rotor aircraft system using a continuous sliding mode control. The sensing of altitude measurement sensing is performed by a pressure sensor in order to obtain a robust altitude control of the vehicle in hovering mode both indoor and outdoor. The altitude measurement has the advantage of introducing this state information directly in the closed loop control which should be very useful for achieving robust stabilization of the altitude control. Accordingly, we propose a sliding mode control strategy without chattering. The sliding mode control proposed removes the chattering phenomenon by replacing a sign function with a high-slope saturation function. The control algorithm is derived from the Lyapunov stability theorem. Moreover, we have assumed that the actuators are able to respond quickly and accurately and we have not enforced limits on the control signals for a real-time application. Finally, to verify the satisfactory performance of proposed nonlinear control law, several simulations and experimental results of the Chattering-free sliding mode control for the Quad-rotor aircraft in the presence of bounded disturbances are presented.

Robust Fault Diagnosis for Quadrotor UAVs Using Adaptive Thau Observer

Abstract: A robust Fault Diagnosis (FD) scheme for a real quadrotor Unmanned Aerial Vehicle (UAV) is proposed in this paper. Firstly, a novel Adaptive Thau observer (ATO) is developed to estimate the quadrotor system states and build a set of offset residuals to indicate actuators' faults. Based on these residuals, some rules of Fault Diagnosis (FD) are designed to detect and isolate the faults as well as estimate the fault offset parameters. Secondly, a synthetic robust optimization scheme is presented to improve Fault Estimation (FE) accuracies, three key issues include modeling uncertainties, and magnitude order unbalances as well as noises are addressed. Finally, a typical fault of rotors is simulated and injected into one of four rotors of the quadrotor, and experiments for the FD scheme have been carried out. Unlike former research works on the FD schemes for quadrotors, our proposed FD scheme based on the ATO can not only detect and isolate the failed actuators, but also estimate the fault severities. Regardless of roughness of the real flying data, the FD results still have sufficient FE accuracies.

Control of a Mobile Robot Subject to Wheel Slip

Abstract: Wheel slip is inevitable when a Wheeled Mobile Robot (WMR) is moving at a high speed or on a slippery surface. In particular, when neither lateral nor longitudinal slips can be ignored in the dynamic model, a WMR becomes an under-actuated nonlinear dynamic system. To study the maneuverability of a WMR in such a realistic environment, we model the overall WMR dynamics subject to wheel slip and propose control algorithms in regulation control and turning control tasks for the WMR. In regulation control, a time-invariant discontinuous feedback law is developed to asymptotically stabilize the system to the desired configuration with exponential convergence rate. In turning control, a sliding mode-based extremum seeking control technique is applied to achieve stable and sharp turning. Simulation results are presented to validate the theoretical results.

Relative Navigation Approach for Vision-Based Aerial GPS-Denied Navigation

Abstract: GPS-denied aerial flight is a challenging research problem and requires knowledge of complex elements from several distinct disciplines. Additionally, aerial vehicles can present challenging constraints such as stringent payload limits and fast vehicle dynamics. In this paper we propose a new architecture to simplify some of the challenges that constrain GPS-denied aerial flight. At the core, the approach combines visual graph-SLAM with a multiplicative extended Kalman filter. More importantly, for the front end we depart from the common practice of estimating global states and instead keep the position and yaw states of the MEKF relative to the current node in the map. This relative navigation approach provides simple application of sensor measurement updates, intuitive definition of map edges and covariances, and the flexibility of using a globally consistent map when desired. We verify the approach with hardware flight-test results.

Dynamic Task Assignment and Path Planning for Multi-AUV System in Variable Ocean Current Environment

Abstract: An integrated multiple autonomous underwater vehicle (multi-AUV) dynamic task assignment and path planning algorithm is proposed by combing the improved self-organizing map (SOM) neural network and a novel velocity synthesis approach. Each target is to be visited by one and only one AUV, and a shortest path between a starting point and the destination is found in the presence of the variable current environment and dynamic targets. Firstly, the SOM neuron network is developed to assign a team of AUVs to achieve multiple target locations in dynamic ocean environment. The working process involves special definition of the rule to select the winner, the computation of the neighborhood function, and the method to update weights. Then, the velocity synthesis approach is applied to plan a shortest path for each AUV to visit the corresponding target in dynamic environment subject to the ocean current being variable and targets being movable. Lastly, to demonstrate the effectiveness of the proposed approach, simulation results are given in this paper.

Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots

Abstract: In this work a neural indirect sliding mode control method for mobile robots is proposed. Due to the nonholonomic property and restricted mobility, the trajectory tracking of this system has been one of the research topics for the last ten years. The proposed control structure combines a feedback linearization model, based on a kinematics nominal model, and a practical design that combines an indirect neural adaptation technique with sliding mode control to compensate the dynamics of the robot. Using an online adaptation scheme, a neural sliding mode controller is used to approximate the equivalent control in the neighbourhood of the sliding manifold. A sliding control is appended to ensure that the neural sliding mode control can achieve a stable closed-loop system for the trajectory-tracking control of a mobile robot with unknown nonlinear dynamics. The proposed design simultaneously guarantees the stability of the adaptation of the neural nets and obtains suitable equivalent control when the parameters of the robot model are unknown in advance. The robust adaptive scheme is applied to a mobile robot and shown to be able to guarantee that the output tracking error will converge to zero.

A Review on Fault Diagnosis and Fault Tolerant Control Methods for Single-rotor Aerial Vehicles

Abstract: Faults or failures are inevitable to occur and their prompt detection and isolation are essential for the dependability of various systems and for avoiding damages to the system itself, persons and the environment. Therefore, the safety of helicopter platforms have attracted the attention of many researchers in the past two decades. In order to deal with these problems, this paper presents an overview of the recent development and current researches in the field of fault diagnosis, including analytical/model-based, signal processing-based and knowledge-based techniques, and also passive/active fault- tolerant control approaches. Among various helicopters, single-rotor aerial vehicles, i.e. manned helicopters, unmanned helicopters, two and three degree-of-freedom unmanned helicopter experimental platforms, are considered for providing an overall picture of the fault diagnosis and fault-tolerant control approaches based on the review of journal articles in last two decades, conference articles in last several years and some books.

Nonlinear Trajectory Control of Multi-body Aerial Manipulators

Abstract: This paper studies trajectory control of aerial vehicles equipped with robotic manipulators. The proposed approach employs free-flying multi-body dynamics modeling and backstepping control to develop stabilizing control laws for a class of underactuated aerial systems. Two control methods are developed: coordinate-based and coordinate-free which are both generally applicable to aerial manipulation tasks. A simulated hexrotor vehicle equipped with a simple manipulator is employed to demonstrate the proposed techniques.

PID Controller Applied to Hexacopter Flight

Abstract: In the last decades, the increasing interest in unmanned aerial vehicles for both military and civil applications made necessary the development of flight control theory and algorithms more and more efficient and fast. In this paper, an original trajectory controller, like a Proportional Integrative Derivative one, is taken into account and the drone structure assumes a hexacopter configuration, i.e. it consists of six rotors, located on the vertices of a regular hexagon with three pairs of counter-rotating fixed pitch blades. The motion of unmanned aerial vehicle is described by means of the Newton-Euler equations in terms of quaternions, in order to improve the numerical efficiency and stability of the controller algorithm, whose novelty lies in the quaternion error definition. Both model and algorithm have been tested and then validated through a wide experimentation, where the drone keeps going to not elementary trajectories.

Command Filter Based Robust Nonlinear Control of Hypersonic Aircraft with Magnitude Constraints on States and Actuators

Abstract: The command filter based robust nonlinear controller is designed for the longitudinal dynamics of a generic hypersonic aircraft in presence of parametric model uncertainty and magnitude constraints on the states and actuators. The functional subsystems are transformed into the linearly parameterized form and the controller is proposed based on dynamic inversion and adaptive gain. Since the dynamics are with cascade structure, the states are considered as virtual control and the signal is filtered to produce the limited command signal and its derivative. To eliminate the effect of the constraint, the auxiliary error compensation design is employed and the parameter projection estimation is proposed based on the compensated tracking error. The uniformly ultimately boundedness is guaranteed for the closed-loop control system. Simulation results show that the proposed approach achieves good tracking performance.

Autonomous Landing of MAVs on an Arbitrarily Textured Landing Site Using Onboard Monocular Vision

Abstract: This paper presents a novel solution for micro aerial vehicles (MAVs) to autonomously search for and land on an arbitrary landing site using real-time monocular vision. The autonomous MAV is provided with only one single reference image of the landing site with an unknown size before initiating this task. We extend a well-known monocular visual SLAM algorithm that enables autonomous navigation of the MAV in unknown environments, in order to search for such landing sites. Furthermore, a multi-scale ORB feature based method is implemented and integrated into the SLAM framework for landing site detection. We use a RANSAC-based method to locate the landing site within the map of the SLAM system, taking advantage of those map points associated with the detected landing site. We demonstrate the efficiency of the presented vision system in autonomous flights, both indoor and in challenging outdoor environment.

Adaptive Neural Network Finite-Time Control for Uncertain Robotic Manipulators

Abstract: An adaptive neural network finite-time controller (NNFTC) for a class of uncertain nonlinear systems is proposed by using the backstepping method, which employs an adaptive neural network (NN) system to approximate the structure uncertainties and uses a variable structure term to compensate the approximation errors, thus improving the robustness of the system to external disturbances The controller is then applied to uncertain robotic manipulators, with a control objective of driving the system state to the original equilibrium point It is proved that the closed-loop system is finite-time stable Moreover, simulated and experimental results indicate that the proposed NNFTC is effective and robust