Exploiting Heterogeneity in Networks of Aerial and Ground Robotic Agents

By taking advantage of complementary communication technologies, distinct sensing functionalities and varied motion dynamics present in a heterogeneous multi-robotic network, it is possible to accomplish a main mission objective by assigning specialized sub-tasks to specific members of a robotic team. An adequate selection of the team members and an effective coordination are some of the challenges to fully exploit the unique capabilities that these types of systems can offer. Motivated by real world applications, we focus on a multi-robotic network consisting off aerial and ground agents which has the potential to provide critical support to humans in complex settings. For instance, aerial robotic relays are capable of transporting small ground mobile sensors to expand the communication range and the situational awareness of first responders in hazardous environments. In the first part of this dissertation, we extend work on manipulation of cable-suspended loads using aerial robots by solving the problem of lifting the cable-suspended load from the ground before proceeding to transport it. Since the suspended load-quadrotor system experiences switching conditions during this critical maneuver, we define a hybrid system and show that it is differentially-flat. This property facilitates the design of a nonlinear controller which tracks a waypoint-based trajectory associated with the discrete states of the hybrid system. In addition, we address the case of unknown payload mass by combining a least-squares estimation method with the designed controller. Second, we focus on the coordination of a heterogeneous team formed by a group of ground mobile sensors and a flying communication router which is deployed to sense areas of interest in a cluttered environment. Using potential field methods, we propose a controller for the coordinated mobility of the team to guarantee inter-robot and obstacle collision avoidance as well as connectivity maintenance among the ground agents while the main goal of sensing is carried out. For the case of the aerial communications relays, we combine antenna diversity with reinforcement learning to dynamically re-locate these relays so that the received signal strength is maintained above a desired threshold. Motivated by the recent interest of combining radio frequency and optical wireless communications, we envision the implementation of an optical link between micro-scale aerial and ground robots. This type of link requires maintaining a sufficient relative transmitter-receiver position for reliable communications. In the third part of this thesis, we tackle this problem. Based on the link model, we define a connectivity cone where a minimum transmission rate is guaranteed. For example, the aerial robot has to track the ground vehicle to stay inside this cone. The control must be robust to noisy measurements. Thus, we use particle filters to obtain a better estimation of the receiver position and we design a control algorithm for the flying robot to enhance the transmission rate. Also, we consider the problem of pairing a ground sensor with an aerial vehicle, both equipped with a hybrid radio-frequency/optical wireless communication system. A challenge is positioning the flying robot within optical range when the sensor location is unknown. Thus, we take advantage of the hybrid communication scheme by developing a control strategy that uses the radio signal to guide the aerial platform to the ground sensor. Once the optical-based signal strength has achieved a certain threshold, the robot hovers within optical range. Finally, we investigate the problem of building an alliance of agents with different skills in order to satisfy the requirements imposed by a given task. We find this alliance, known also as a coalition, by using a bipartite graph in which edges represent the relation between agent capabilities and required resources for task execution. Using this graph, we build a coalition whose total capability resources can satisfy the task resource requirements. Also, we study the heterogeneity of the formed coalition to analyze how it is affected for instance by the amount of capability resources present in the agents

Design of an UAV swarm

This master thesis tries to give an overview on the general aspects involved in the design of an UAV swarm. UAV swarms are continuoulsy gaining popularity amongst researchers and UAV manufacturers, since they allow greater success rates in task accomplishing with reduced times. Appart from this, multiple UAVs cooperating between them opens a new field of missions that can only be carried in this way. All the topics explained within this master thesis will explain all the agents involved in the design of an UAV swarm, from the communication protocols between them, navigation and trajectory analysis and task allocation

Parameter-robust linear quadratic Gaussian technique for multi-agent slung load transportation

This paper copes with parameter-robust controller design for transportation system by multiple unmanned aerial vehicles. The transportation is designed in the form of string connection. Minimal state-space realization of slung-load dynamics is obtained by Newtonian approach with spherical coordinates. Linear quadratic Gaussian / loop transfer recovery (LQG/LTR) is implemented to control the position and attitude of all the vehicles and payloads. The controller's robustness against variation of payload mass is improved using parameter-robust linear quadratic Gaussian (PRLQG) method. Numerical simulations are conducted with several transportation cases. The result verifies that LQG/LTR shows fast performance while PRLQG has its strong point in robustness against system variation

Real-time control architecture for a multi UAV test bed

The purpose of this thesis is to develop a control architecture running at real-time for a multi unmanned aerial vehicle test bed formed by three AscTec Hummingbird mini quadrotors. The reliable and reconfigurable architecture presented here has a FPGA-based embedded system as main controller. Under the implemented control system, different practical applications have been performed in the MARHES Lab at the University of New Mexico as part of its research in cooperative control of mobile aerial agents. This thesis also covers the quadrotor modeling, the design of a position controller, the real-time architecture implementation and the experimental flight tests. A hybrid approach combining first-principles with system identification techniques is used for modeling the quadrotor due to the lack of information around the structure of the onboard controller designed by AscTec. The complete quadrotor model structure is formed by a black-box subsystem and a point-mass submodel. Experimental data have been gathered for system identification and black-box submodel validation purposes; while the point-mass submodel is found applying rigid-body dynamics. Using the dynamical model, a position control block based in lead-lag and PI compensators is developed and simulated. Improvements in trajectory tracking performance are achieved estimating the linear velocity of the aerial robot and incorporating velocity lead-lag compensators to the control approach. The velocity of the aerial robot is computed by numerical differentiation of position data. Simulation results to a variety of input signals of the control block in cascade with the complete dynamic model of the quadrotor are included. The control block together with the velocity estimation is fully programmed in the embedded controller. A graphical user interface, GUI, as part of the architecture is designed to display real-time data of position and orientation streamed from the motion tracking system as well as to contain useful user controllers. This GUI facilitates that a single operator conducts and oversees all aspects of the different applications where one or multiple quadrotors are used. Experimental tests have helped to tune the control parameters determined by simulation. The performance of the whole architecture has been validated through a variety of practical applications. Autonomous take off, hovering and landing, target surveillance, trajectory tracking and suspended payload transportation are just some of the applications carried out employing the real-time control architecture proposed in this thesis

Multi-agent Collision Avoidance Using Interval Analysis and Symbolic Modelling with its Application to the Novel Polycopter

Coordination is fundamental component of autonomy when a system is defined by multiple mobile agents. For unmanned aerial systems (UAS), challenges originate from their low-level systems, such as their flight dynamics, which are often complex. The thesis begins by examining these low-level dynamics in an analysis of several well known UAS using a novel symbolic component-based framework. It is shown how this approach is used effectively to define key model and performance properties necessary of UAS trajectory control. This is demonstrated initially under the context of linear quadratic regulation (LQR) and model predictive control (MPC) of a quadcopter. The symbolic framework is later extended in the proposal of a novel UAS platform, referred to as the ``Polycopter" for its morphing nature. This dual-tilt axis system has unique authority over is thrust vector, in addition to an ability to actively augment its stability and aerodynamic characteristics. This presents several opportunities in exploitative control design. With an approach to low-level UAS modelling and control proposed, the focus of the thesis shifts to investigate the challenges associated with local trajectory generation for the purpose of multi-agent collision avoidance. This begins with a novel survey of the state-of-the-art geometric approaches with respect to performance, scalability and tolerance to uncertainty. From this survey, the interval avoidance (IA) method is proposed, to incorporate trajectory uncertainty in the geometric derivation of escape trajectories. The method is shown to be more effective in ensuring safe separation in several of the presented conditions, however performance is shown to deteriorate in denser conflicts. Finally, it is shown how by re-framing the IA problem, three dimensional (3D) collision avoidance is achieved. The novel 3D IA method is shown to out perform the original method in three conflict cases by maintaining separation under the effects of uncertainty and in scenarios with multiple obstacles. The performance, scalability and uncertainty tolerance of each presented method is then examined in a set of scenarios resembling typical coordinated UAS operations in an exhaustive Monte-Carlo analysis

Armstrong Flight Research Center Research Technology and Engineering Report 2015

I am honored to endorse the 2015 Neil A. Armstrong Flight Research Centers Research, Technology, and Engineering Report. The talented researchers, engineers, and scientists at Armstrong are continuing a long, rich legacy of creating innovative approaches to solving some of the difficult problems and challenges facing NASA and the aerospace community.Projects at NASA Armstrong advance technologies that will improve aerodynamic efficiency, increase fuel economy, reduce emissions and aircraft noise, and enable the integration of unmanned aircraft into the national airspace. The work represented in this report highlights the Centers agility to develop technologies supporting each of NASAs core missions and, more importantly, technologies that are preparing us for the future of aviation and space exploration.We are excited about our role in NASAs mission to develop transformative aviation capabilities and open new markets for industry. One of our key strengths is the ability to rapidly move emerging techniques and technologies into flight evaluation so that we can quickly identify their strengths, shortcomings, and potential applications.This report presents a brief summary of the technology work of the Center. It also contains contact information for the associated technologists responsible for the work. Dont hesitate to contact them for more information or for collaboration ideas

Armstrong Flight Research Center Research Technology and Engineering 2017

I am delighted to present this report of accomplishments at NASA's Armstrong Flight Research Center. Our dedicated innovators possess a wealth of performance, safety, and technical capabilities spanning a wide variety of research areas involving aircraft, electronic sensors, instrumentation, environmental and earth science, celestial observations, and much more. They not only perform tasks necessary to safely and successfully accomplish Armstrong's flight research and test missions but also support NASA missions across the entire Agency. Armstrong's project teams have successfully accomplished many of the nation's most complex flight research projects by crafting creative solutions that advance emerging technologies from concept development and experimental formulation to final testing. We are developing and refining technologies for ultra-efficient aircraft, electric propulsion vehicles, a low boom flight demonstrator, air launch systems, and experimental x-planes, to name a few. Additionally, with our unique location and airborne research laboratories, we are testing and validating new research concepts. Summaries of each project highlighting key results and benefits of the effort are provided in the following pages. Technology areas for the projects include electric propulsion, vehicle efficiency, supersonics, space and hypersonics, autonomous systems, flight and ground experimental test technologies, and much more. Additional technical information is available in the appendix, as well as contact information for the Principal Investigator of each project. I am proud of the work we do here at Armstrong and am pleased to share these details with you. We welcome opportunities for partnership and collaboration, so please contact us to learn more about these cutting-edge innovations and how they might align with your needs

Wide-Area Surveillance System using a UAV Helicopter Interceptor and Sensor Placement Planning Techniques

This project proposes and describes the implementation of a wide-area surveillance system comprised of a sensor/interceptor placement planning and an interceptor unmanned aerial vehicle (UAV) helicopter. Given the 2-D layout of an area, the planning system optimally places perimeter cameras based on maximum coverage and minimal cost. Part of this planning system includes the MATLAB implementation of Erdem and Sclaroff’s Radial Sweep algorithm for visibility polygon generation. Additionally, 2-D camera modeling is proposed for both fixed and PTZ cases. Finally, the interceptor is also placed to minimize shortest-path flight time to any point on the perimeter during a detection event. Secondly, a basic flight control system for the UAV helicopter is designed and implemented. The flight control system’s primary goal is to hover the helicopter in place when a human operator holds an automatic-flight switch. This system represents the first step in a complete waypoint-navigation flight control system. The flight control system is based on an inertial measurement unit (IMU) and a proportional-integral-derivative (PID) controller. This system is implemented using a general-purpose personal computer (GPPC) running Windows XP and other commercial off-the-shelf (COTS) hardware. This setup differs from other helicopter control systems which typically use custom embedded solutions or micro-controllers. Experiments demonstrate the sensor placement planning achieving \u3e90% coverage at optimized-cost for several typical areas given multiple camera types and parameters. Furthermore, the helicopter flight control system experiments achieve hovering success over short flight periods. However, the final conclusion is that the COTS IMU is insufficient for high-speed, high-frequency applications such as a helicopter control system