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Giuseppe Silano's Ph.D. Thesis - Advisor: Prof. Dr. Luigi Iannelli
Abstract
Aerial robotics is a fast-growing field of robotics and in particular multi-rotor aircraft are rapidly increasing in popularity also out of the scientific community. However, designing autopilots for these vehicles is a challenging task, which involves multiple interconnected aspects. Hence, having tools able to show what happens when some new applications are going to be developed in unknown or critical situations is more and more important for the whole design process. The aim of this thesis is to show the role and the effectiveness of robotics simulators in flight control system design for multi-rotor aircraft (especially, quad-rotors) proposing a Software-in-the-loop (SIL) methodology. In particular, it will be explained, by using rather complex examples, how a SIL approach allows to detect and to manage instabilities that otherwise might not arise when considering the only MATLAB/Simulink simulations. On the other hand, such instabilities may not be just related to the complexity, accuracy, or detailed modeling of the simulated plant, but rather they may appear due to peculiar features of the final realization and, in particular, the software that will implement the control strategy. Indeed, aspects like synchronization, overflow, task communication, are all managed by libraries or tools available during the control design phase, and yet they are specific of the final code implementation. From such a perspective, SIL simulation has to be considered a valuable tool for discovering, in an earlier phase of the usual V-model process, those issues that Model-in-the-loop (MIL) simulation does not necessarily detect. At the same time, a SIL simulation, obtained by using realistic and detailed simulators give the opportunity of validating in an easy way the effects of modifying the control strategy for complex missions. That represents quite often the easiest way to tune the flight control system and to check its validity. Although advantages of such methodology are reasonable for the scientific community from a very general viewpoint, illustrative case studies can be of interest in particular if declined to the specific application.
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Unmanned Aerial Vehicles (UAVs) have multi-domain applications, fixed-wing UAVsbeing a widely used class. Despite the ongoing research on the topics of guidance and formationcontrol of fixed-wing UAVs, little progress is known on implementation of semi-physical validationplatforms (software-in-the-loop or hardware-in-the-loop) for such complex autonomous systems.A semi-physical simulation platform should capture not only the physical aspects of UAV dynamics,but also the cybernetics aspects such as the autopilot and the communication layers connectingthe different components. Such a cyber-physical integration would allow validation of guidanceand formation control algorithms in the presence of uncertainties, unmodelled dynamics, low-levelcontrol loops, communication protocols and unreliable communication: These aspects are oftenneglected in the design of guidance and formation control laws for fixed-wing UAVs. This paperdescribes the development of a semi-physical platform for multi-fixed wing UAVs where all theaforementioned points are carefully integrated. The environment adopts Raspberry Pi’s programmedin C++, which can be interfaced to standard autopilots (PX4) as a companion computer. Simulationsare done in a distributed setting with a server program designed for the purpose of routing databetween nodes, handling the user inputs and configurations of the UAVs. Gazebo-ROS is used asa 3D visualization tool.
Simulation is a standard approach used for designing complex systems like the flight controller in multi-rotor vehicles. In this paper we illustrate how the software-in-the-loop (SIL) methodology allows to detect and manage instabilities of a quadrotor control system that otherwise might not arise when considering only Matlab/Simulink simulations discovering issues that a model-in-the-loop (MIL) simulation does not necessarily detect.
The paper aims to give the reader a practical and concrete evidence of such considerations through the case study of a micro quadrotor.
The trajectory control problem, defined as making a vehicle follow a pre-established path in space, can be solved by means of trajectory tracking or path following. In the trajectory tracking problem a timed reference position is tracked. The path following approach removes any time dependence of the problem, resulting in many advantages on the control performance and design. An exhaustive review of path following algorithms applied to quadrotor vehicles has been carried out, the most relevant are studied in this paper. Then, four of these algorithms have been implemented and compared in a quadrotor simulation platform: Backstepping and Feedback Linearisation control-oriented algorithms and NLGL and Carrot-Chasing geometric algorithms.
Motion control theory applied to multi-rotor aerial vehicles (MAVs) has gained attention with the recent increase in the processing power of computers, which are now able to perform the calculations needed for this technique, and with lower cost of sensors and actuators. Control algorithms of this kind are applied to the position and the attitude of MAVs. In this paper, we present a review of recent developments in position control and attitude control of multi-rotor aerial robots systems. We also point out the growth of related research, starting with the boom in multi-rotor unmanned aerial robotics that began after 2010, and we discuss reported field applications and future challenges of the control problem described here. The objective of this survey is to provide a unified and accessible presentation, placing the classical model of a multi-rotor aerial vehicle and the proposed control approaches into a proper context, and to form a starting point for researchers who are initiating their endeavors in linear/nonlinear position, altitude or attitude control applied to MAVs. Finally, the contribution of this work is an attempt to present a comprehensive review of recent breakthroughs in the field, providing links to the most interesting and most successful works from the state-of-the-art.
The actual performance of model-based path-following methods for Unmanned Aerial Vehicles (UAVs) show considerable dependence on the wind knowledge and on the fidelity of the dynamic model used for design. This work analyzes and demonstrates the performance of an adaptive Vector Field (VF) control law which can compensate for the lack of knowledge of the wind vector and for the presence of unmodelled course angle dynamics. Extensive simulation experiments, calibrated on a commercial fixed-wing UAV and proven to be realistic, show that the new VF method can better cope with uncertainties than its standard version. In fact, while the standard VF approach works perfectly for ideal first-order course angle dynamics (and perfect knowledge of the wind vector), its performance degrades in the presence of unknown wind or unmodelled course angle dynamics. On the other hand, the estimation mechanism of the proposed adaptive VF effectively compensates for wind uncertainty and unmodelled dynamics, sensibly reducing the path-following error as compared to the standard VF.
In recent years, there has been a strong activity in the so-called precision agriculture, particularly the monitoring aspect, not only to improve productivity, but also to meet demand of a growing population. At a large scale, precise monitoring of cultivated fields is a quite challenging task. Therefore, this paper aims to propose a survey on techniques, applied to precision agriculture monitoring, through the use of drones equipped with multispectral, thermal and visible cameras. For each application, the main limitations are highlighted and the parameters to be considered before to perform a flight are reported.
The manipulation of large objects by robotic systems is a challenge for applications in the construction industry, industrial decommissioning, and urban search and rescue (USAR). These are associated with dangerous environments and thus motivate devising robotic solutions to replace human presence. Furthermore, they often require manipulation of long objects, such as pipes, bars, beams, and metal frameworks, with limited access to their center of mass (CoM).
Underwater manipulation is a challenging problem. The state-of-the-art technology is dominated by remotely operated vehicles (ROVs). ROV operations typically require an offshore crew consisting of, at minimum, an intendant (or supervisor), an operator, and a navigator. This crew must often be doubled or even tripled due to work shifts. In addition, customer representatives often wish to be physically present offshore. Furthermore, underwater intervention missions are still dominated by a significant amount of lowlevel, manual control of the manipulator(s) and of the vehicle itself. While there is a significant amount of research on autonomous underwater vehicles (AUVs) in general and fieldable solutions already exist for inspection and exploration missions, possibilities remain for adding intelligent autonomous functions for interventions.
This paper summarizes new aerial robotic manipulation technologies and methods, required for outdoor industrial inspection and maintenance, developed in the AEROARMS project. It presents aerial robotic manipulators with dual arms and multi-directional thrusters. It deals with the control systems, including the control of the interaction forces and the compliance, the teleoperation, which uses passivity to tackle the trade-off between stability and performance, perception methods for localization, mapping and inspection, and planning methods, including a new control-aware approach for aerial manipulation. Finally, it describes a novel industrial platform with multi-directional thrusters and a new arm design to increase the robustness in industrial contact inspections. The lessons learned in the application to outdoor aerial manipulation for inspection and maintenance are pointed out.
Context: Embedded systems have overwhelming penetration around the world. Innovations are increasingly triggered by software embedded in automotive, transportation, medical-equipment, communication, energy, and many other types of systems. To test embedded software in an effective and efficient manner, a large number of test techniques, approaches, tools and frameworks have been proposed by both practitioners and researchers in the last several decades. Objective: However, reviewing and getting an overview of the entire state-of-the-art and the –practice in this area is challenging for a practitioner or a (new) researcher. Also unfortunately, as a result, we often see that many companies reinvent the wheel (by designing a test approach new to them, but existing in the domain) due to not having an adequate overview of what already exists in this area. Method: To address the above need, we conducted and report in this paper a systematic literature review (SLR) in the form of a systematic literature mapping (SLM) in this area. After compiling an initial pool of 588 papers, a systematic voting about inclusion/exclusion of the papers was conducted among the authors, and our final pool included 312 technical papers. Results: Among the various aspects that we aim at covering, our review covers the types of testing topics studied, types of testing activity, types of test artifacts generated (e.g., test inputs or test code), and the types of industries in which studies have focused on, e.g., automotive and home appliances. Furthermore, we assess the benefits of this review by asking several active test engineers in the Turkish embedded software industry to review its findings and provide feedbacks as to how this review has benefitted them. Conclusion: The results of this review paper have already benefitted several of our industry partners in choosing the right test techniques / approaches for their embedded software testing challenges. We believe that it will also be useful for the large world-wide community of software engineers and testers in the embedded software industry, by serving as an “index” to the vast body of knowledge in this important area. Our results will also benefit researchers in observing the latest trends in this area and for identifying the topics which need further investigations.
This paper deals with the problem of trajectory planning and tracking of a quadcopter system based on the property of differential flatness. Firstly, B-splines characterizations of the flat output allow for optimal trajectory generation subject to waypoints constraints, thrust and angles constraints while minimizing the trajectory length. Secondly, the proposed tracking control strategy combines feedback linearization and nested saturation control via flatness. The control strategy provides bounded inputs (thrust, roll and pitch angles) while ensuring the overall stability of the tracking error dynamics. The control parameters are chosen based on the information of the a priori given reference trajectory. Moreover, conditions for the existence of these parameters are presented. The effectiveness of the trajectory planning and the tracking control design are analyzed and validated through simulation and experiments results over a real nano quadcopter platform, the Crazyflie 2.0.
Quadrotor aircraft are drawing considerable attention for their high mobility and capacity to perform tasks with complete autonomy, while minimizing the costs and risks involved with the direct intervention of human operators. Moreover, several limitations characterizing these rotary-wing unmanned aerial systems (UASs), such as their underactuation, make quadrotors ideal testbeds for innovative theoretical approaches to the problem of controlling mechanical systems. Designing autopilots for autonomous quadrotors is a challenging task, which involves multiple interconnected aspects. Numerous researchers are currently addressing the problem of designing autonomous guidance systems, navigation systems, and control systems for quadrotors. The primary goal of this article is to present an analysis and synthesis of several nonlinear robust control systems for quadrotors, as discussed in Summary. First, the article presents and analyzes the equations of motion of quadrotors under three sets of progressively restrictive modeling assumptions: 1) the vehicle's inertial properties (such as the mass and matrix of inertia) vary in time, 2) the quadrotor's main frame is a rigid body and the propellers are thin spinning discs, and 3) the pitch and roll angles are small.
State-of-the-art approaches in quadrotor control split the problem into multiple cascaded subproblems, exploiting the different time scales of the rotational and translational dynamics. They calculate a desired acceleration as input for a cascaded attitude controller but omit the attitude dynamics. These approaches use limits on the desired acceleration to maintain feasibility and robustness through the control cascade. We propose an implementation of an LQR controller, which: (I) is linearized depending on the quadrotor’s state; (II) unifies the control of rotational and translational states; (III) handles time-varying system dynamics and control parameters. Our implementation is efficient enough to compute the full linearization and solution of the LQR at a minimum of 10Hz on the vehicle using a common ARM processor. We show four successful experiments: (I) controlling at hover state with large disturbances; (II) tracking along a trajectory; (III) tracking along an infeasible trajectory; (IV) tracking along a trajectory with disturbances. All the experiments were done using only onboard visual inertial state estimation and LQR computation. To the best of our knowledge, this is the first implementation and evaluation of a state-dependent LQR capable of onboard computation while providing this amount of versatility and performance. Video of the experiments: https://youtu.be/8OVsJNgNfa0 Narrated video presentation: https://youtu.be/c7gHF-NJjPo
The quadrotor task of negotiating aggressive attitude maneuvers while adhering to motor constraints is addressed here. The majority of high level quadrotor Nonlinear Control System (NCS) solutions ignore motor control authority limitations , especially important during aggressive attitude maneuvers, generating unrealizable thrusts and negating the validity of the accompanying stability proofs. Here, an attitude control framework is developed, comprised by a thrust allocation strategy and a specially designed geometric attitude tracking controller, allowing the quadrotor to achieve aggressive attitude maneuvers, while complying to actuator constraints and simultaneously staying "close" to a desired position command in a computa-tionally inexpensive way. This is a novel contribution resulting in thrusts realizable by available quadrotors during aggressive attitude maneuvers, and enhanced performance guaranteed by valid stability proofs. Also, it is shown that the developed controller can be combined with a collective thrust expression in producing a position/yaw tracking controller. Through rigorous stability proofs, both the position and attitude frameworks are shown to have desirable closed loop properties that are almost global. This establishes a quadrotor control solution allowing the vehicle to negotiate aggressive maneuvers position/attitude on SE(3). Simulations illustrate and validate the effectiveness and capabilities of the developed solution.
In this paper, we prove that the dynamical model of a quadrotor subject to linear rotor drag effects is differentially flat in its position and heading. We use this property to compute feed-forward control terms directly from a reference trajectory to be tracked. The obtained feed-forward terms are then used in a cascaded, nonlinear feedback control law that enables accurate agile flight with quadrotors. Compared to state-of-the-art control methods, which treat the rotor drag as an unknown disturbance, our method reduces the trajectory tracking error significantly. Finally, we present a method based on a gradient-free optimization to identify the rotor drag coefficients which are required to compute the feed-forward control terms. The new theoretical results are thoroughly validated trough extensive comparative experiments.
The main motivation of this work is to propose the simulation-in-the-loop approach for educational purposes within the UAV field. In particular the visual-based object tracking problem is illustrated through the use of the MathWorks Virtual Reality Toolbox together with MATLAB, by simulating the behavior of a drone in a 3D environment when detection, tracking and control algorithms are run. Matlab VR has been chosen due to the familiarity that students have with. In this way the attention can be moved to the classifier, the tracker, the references generator and the trajectory tracking control. The overall archietcture is quite modular so that each block can be easily replaced with others thus simplifying the development phase. A simple case study has been presented in order to show the effectiveness of the approach.
This tutorial chapter will teach readers how to use ROS to fly a small quadcopter both individually and as a group. We will discuss the hardware platform, the Bitcraze Crazyflie 2.0, which is well suited for swarm robotics due to its small size and weight. After first introducing the crazyflie_ros stack and its use on an individual robot, we will extend scenarios of hovering and waypoint following from a single robot to the more complex multi-UAV case. Readers will gain insight into physical challenges, such as radio interference, and how to solve them in practice. Ultimately, this chapter will prepare readers not only to use the stack as-is, but also to extend it or to develop their own innovations on other robot platforms.
Cooperation among multiple aerial vehicles could provide a solution for overcoming limited payload restrictions. Multiple aerial vehicles can carry a heavy or large object safely by sharing the load, alleviating the risk involved in exerting considerable inertia on a single vehicle.
State-of-the-art work on deformable multirotor aerial robots has developed a strong maneuvering ability in such robots, whereas there is no versatile aerial robot that can perform both deforming maneuvering and aerial manipulation yet. However, a novel multilinked aerial robot presented in our previous work, called DRAGON, has both potential because of its serial-link structure. Therefore, an online motion planning method for such a multilinked aerial robot is required. In this letter, we first reveal the general statics model of the multilinked aerial robot, which involves the influence of joint torque, rotor thrust force, external wrench, and gravity, and further discuss the necessary rotor thrust force and joint torque required to compensate for external force and gravity under the quasi-static assumption. Then, we propose a real-time motion planning method, which sequentially solves the differential kinematics problem. This method considers the limitations of rotor thrust force and joint torque, as well as kinematics constraints. Furthermore, we introduce the integrated control framework, which can follow a quasi-static multilinks’ trajectory and compensate for the external wrench. Finally, experiments to squeeze a virtual hatch covered by a movable plate are performed with quad-type
DRAGON
to demonstrate the feasibility of the proposed motion planning method in real-time.
Simulation is a standard approach used for designing complex systems like the flight controller in multi-rotor vehicles. In this paper we illustrate how the software-in-the-loop (SIL) methodology allows to detect and manage instabilities of a quadrotor control system that otherwise might not arise when considering only Matlab/Simulink simulations. The use of the SIL technique allows to understand the behavior of the flight control system by comparing and evaluating different scenarios, with a details level quite close to reality. At the same time, it is possible to discover issues that a model-in-the-loop (MIL) simulation does not necessarily detect, even if carried out through a multi-physics co-simulation approach. The paper aims to give the reader a practical and concrete evidence of such considerations through the case study of a micro quadrotor.
This chapter proposes a typical use case dealing with the physical simulation of autonomous robots (specifically, quadrotors) and their interfacing through ROS (Robot Operating System). In particular, we propose CrazyS, an extension of the ROS package RotorS, aimed to modeling, developing and integrating the Crazyflie 2.0 nano-quadcopter in the physics based simulation environment Gazebo. Such simulation platform allows to understand quickly the behavior of the flight control system by comparing and evaluating different indoor and outdoor scenarios, with a details level quite close to reality. The proposed extension, running on Kinetic Kame ROS version but fully compatible with the Indigo Igloo one, expands the RotorS capabilities by considering the Crazyflie 2.0 physical model, its flight control system and the Crazyflie's on-board IMU, as well. A simple case study has been considered in order to show how the package works and how the dynamical model interacts with the control architecture of the quad-copter. The contribution can be also considered as a reference guide for expanding the RotorS functionalities in the UAVs field, by facilitating the integration of new aircrafts. We released the software as open-source code, thus making it available for scientific and educational activities.
Discusses various robot competitions held in Europe. The European Robotics League (ERL) is a novel pan-European competition format that aims to provide a platform for developing, benchmarking, and showcasing challenging robotics technologies, bridging the gap between industry, research, and the general public. It builds on the success of important European competitions and on several EU-FP7/H2020 projects. In addition to the major emergency robot tournaments, several local tournaments are organized each year. In July 2018, the NATO Science and Technology Organization's Center for Maritime Research and Experimentation hosted a local tournament of the ERL Emergency Robots League in La Spezia, Italy. Reports on the variety of competitions held and the involvement of different robotic technologies.
The IEEE Robotics and Automation Society Technical Committee (RAS-TC) has contributed to promoting the emergence of new concepts and technologies as well as new applications. It has also provided services such as the assessment of regulations for development, which play an important role in the consolidation of the applications. The committee received the award for the Most Active IEEE Robotics and Automation Society at the IEEE International Conference on Robotics and Automation (ICRA) in 2016.
The research focus in aerial robotics is shifting from contactless inspection toward interaction and manipulation, with the number of potential applications rapidly increasing [1]. Eventually, aerial manipulators, i.e., unmanned aerial vehicles (UAVs) equipped with manipulators, will likely take on hazardous maintenance tasks now performed by humans. For this to happen, aerial manipulators must be able to perform all the different operations required in these maintenance routines.
Extending the maneuverability of multirotors promises to yield a considerable increase in their scope of applications, such as carrying out more challenging inspection tasks and generating complex, uninterrupted movements of an attached camera. In this article, we address the promise of multirotor maneuverability by presenting Voliro, a novel aerial platform that combines the advantages of existing multirotor systems with the agility of vehicles having omniorientational controllability. In other words, Voliro can fly in any direction while maintaining an arbitrary orientation.
This article deals with the stationary flight control problem of an Unmanned Aircraft Vehicle (UAV) flying in a wind field. The main objective is to develop a robust control law to stabilize the drone flying under real-life outdoor conditions while maintaining adequate flight performances. To do so, a generic nonlinear dynamic model of the quadcopter is firstly developed; this model is then completed with the modeling of the wind disturbances, which allows the simulation of the proposed control algorithms. Two approaches for the synthesis of the control laws are compared: the first one uses Linear Quadratic Regulator (LQR) synthesis and the second one uses structured H∞ synthesis. Simulations are conducted to evaluate the performances of both control laws when subjected to a nominal wind step input varying from 0 to 14 m/s. This particular input choice makes it possible to analyze the performance of the controllers in both transient (wind gust) and steady states (sustained wind). The results show that better performances are obtained with the structured H∞ synthesis using the robust control theory than with the LQR synthesis using the optimal control theory. Furthermore, it is shown that the simplicity of use of the Robust Control Toolbox of MATLAB favors the usage of more complex control architectures without impacting the workload of the control engineer.
This paper presents a literature survey on aerial manipulation. First of all, an extensive study of aerial vehicles and manipulation/interaction mechanisms in aerial manipulation is presented. Various combinations of aerial vehicles and manipulators and their applications in different missions are discussed. Next, two main modeling methods and a detailed investigation of existing estimation and control techniques in aerial manipulation are explained. Finally the shortcomings of current aerial manipulation research are highlighted and a number of directions for future research are suggested.
In this paper a model-free continuous nonlinear control law for the attitude of a quadrotor, based on the Attractive Ellipsoid Method and a saturation term, is proposed. This control law allows the vehicle to track aggressive maneuvers, such as multiple flips about the y axis of the body frame, with high angular velocities. The controller is designed through a singularity-free attitude representation based on a unit quaternion and its gains are computed by solving an optimization problem with LMIs. The proposed controller preserves the advantageous characteristics of the Attractive Ellipsoid Method and increases its robustness properties with the fast response of the nonlinear saturation term, minimizing as much as possible the attitude tracking error and assuring its convergence to a small neighborhood around the origin. A numerical study based on simulations is presented to analyze the advantages of the proposed approach, and experiments are presented to show the performance of the closed-loop system for tracking aggressive multiple flips, even in outdoors.
In this paper we propose CrazyS, an extension of the ROS (Robot Operating System) package RotorS, aimed to modeling, developing and integrating the Crazyflie 2.0 nano-quadcopter in the physics based simulation environment Gazebo. Such simulation platform allows to understand quickly the behavior of the flight control system by comparing and evaluating different indoor and outdoor scenarios, with a details level quite close to reality. The proposed extension expands RotorS capabilities by considering the Crazyflie 2.0 physical model and its flight control system, as well. A simple case study has been considered in order to show how the package works. The use of open-source software makes the platform available for scientific and educational activities.
The use of autonomous vehicles is currently a growing trend, particularly in applications such as manufacturing, hazardous material handling, and surveillance [1]. A quadcopter is an emerging rotorcraft concept for an unmanned aerial vehicle (UAV) that is equipped with four rotors, two pairs of counter-rotating, and fixedpitch blades located at the four corners of the vehicle [2]. In a quadcopter system, yaw is controlled by increasing the angular velocity of rotors that spin in the same direction to a level higher than the velocity of other rotor pairs, and pitch or roll is controlled by increasing the angular velocity of a rotor to a level greater than the velocity of a diametrically opposite rotor (Figure 1) [3].
The advance in robotics has boosted the application of autonomous vehicles to perform tedious and risky tasks or to be cost-effective substitutes for their - man counterparts. Based on their working environment, a rough classi cation of the autonomous vehicles would include unmanned aerial vehicles (UAVs), - manned ground vehicles (UGVs), autonomous underwater vehicles (AUVs), and autonomous surface vehicles (ASVs). UAVs, UGVs, AUVs, and ASVs are called UVs (unmanned vehicles) nowadays. In recent decades, the development of - manned autonomous vehicles have been of great interest, and different kinds of autonomous vehicles have been studied and developed all over the world. In part- ular, UAVs have many applications in emergency situations; humans often cannot come close to a dangerous natural disaster such as an earthquake, a ood, an active volcano, or a nuclear disaster. Since the development of the rst UAVs, research efforts have been focused on military applications. Recently, however, demand has arisen for UAVs such as aero-robotsand ying robotsthat can be used in emergency situations and in industrial applications. Among the wide variety of UAVs that have been developed, small-scale HUAVs (helicopter-based UAVs) have the ability to take off and land vertically as well as the ability to cruise in ight, but their most importantcapability is hovering. Hoveringat a point enables us to make more eff- tive observations of a target. Furthermore, small-scale HUAVs offer the advantages of low cost and easy operation.
In this paper the modeling and control law design for a quadcopter tiltorotor UAV are considered. The problem is developed in a geometric setting to obtain an intrinsic control law which achieves local exponential stability for trajectory tracking on SE(3). Starting from a multi-body system, a simplified model for control design is derived, which allows to handle the actuation constraints in a simpler way. Numerical results are provided to show the enhanced capabilities of the tiltrotor platform with respect to the co-planar rotors configuration and to assess the effectiveness of the control law.
This paper describes a novel Nonlinear Internal Model Control (NLIMC) approach. We show that if we change, in a new manner, the control based on flatness property in order to get a closed loop structure, we can raise the performance and the robustness level with regards to structured or unstructured disturbances. The control performance is evaluated through a Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicle (UAV) where numerical simulations are performed demonstrating the effectiveness of this novel controller form. The obtained results are confirmed by series of experimental tests showing also the robustness level of this technique in presence of wind.
Modern computer vision algorithms typically require expensive data acquisition and accurate manual labeling. In this work, we instead leverage the recent progress in computer graphics to generate fully labeled, dynamic, and photo-realistic proxy virtual worlds. We propose an efficient real-to-virtual world cloning method, and validate our approach by building and publicly releasing a new video dataset, called Virtual KITTI (see http://www.xrce.xerox.com/Research-Development/Computer-Vision/Proxy-Virtual-Worlds), automatically labeled with accurate ground truth for object detection, tracking, scene and instance segmentation, depth, and optical flow. We provide quantitative experimental evidence suggesting that (i) modern deep learning algorithms pre-trained on real data behave similarly in real and virtual worlds, and (ii) pre-training on virtual data improves performance. As the gap between real and virtual worlds is small, virtual worlds enable measuring the impact of various weather and imaging conditions on recognition performance, all other things being equal. We show these factors may affect drastically otherwise high-performing deep models for tracking.
The performance of inertial measurement unit (IMU) is very important for a pedestrian tracker. It is possible for an object to keep track of changes in its own position using an IMU. It is well known that the inertial element acts as the main hardware of IMU, but the accuracy of the inertial sensors degrades with time. The errors are mainly caused by the imperfect structure of the inertial element itself, the change of the internal physical factors and the change of the operating environment, etc. The performances of three IMUs which includes MPU9250, LSM9DS0 and BMX055 are analyzed in this paper. The parameters of the three sensors are compared. The typical error items for inertial elements and the principle and algorithm of the Allan Variance are introduced. Allan Variance technique is used to analyze errors of the inertial sensors. Finally, the design of IMU and the three IMU experimental results are introduced. Final results show that the performance of MPU9250 is the best and BMX055 is the worst.
In general, the starting point for the complex task of designing a robust and efficient control system is the use of nominal models that allow to establish a first set of parameters for the selected control scheme. Once the initial stage of design is achieved, control engineers face the difficult task of Fine-Tuning for a more realistic environment, where the environment conditions are as similar as possible to the real system. For this reason, in the last decades the use of Hardware-in-The-Loop (HiL) systems has been introduced. This simulation technique guarantees realistic simulation environments to test the designs but without danger of damaging the equipment. Also, in this iterative process of Fine-Tuning, it is usual to use different (generally conflicting/opposed) criteria that take into account the sensitivities that always appear in every project, such as economic, security, robustness, performance, for example. In this framework, the use of multi-objective techniques are especially useful since they allow to study the different design alternatives based on the multiple existing criteria. Unfortunately, the combination of multi-objective techniques and verification schemes based on Hardware-In-The-Loop presents a high incompatibility. Since obtaining the optimal set of solutions requires a high computational cost that is greatly increased when using Hardware- In-the-Loop. For this reason, it is often necessary to use less realistic but more computationally efficient verification schemes such as Model in the Loop (MiL), Software in the Loop (SiL) and Processor in the Loop (PiL). In this paper, a combined methodology is presented, where multi-objective optimisation and multi-criteria decision making steps are sequentially performed to achieve a final control solution. The authors claim that while going towards the optimisation sequence over MiL SiL PiL HiL platforms, the complexity of the problem is unveiled to the designer, allowing to state meaningful design objectives. In addition, safety in the step between simulation and reality is significantly increased.