Cooperative Control for Multiple Autonomous Vehicles Using Descriptor Functions

The paper presents a novel methodology for the control management of a swarm of autonomous vehicles. The vehicles, or agents, may have different skills, and be employed for different missions. The methodology is based on the definition of descriptor functions that model the capabilities of the single agent and each task or mission. The swarm motion is controlled by minimizing a suitable norm of the error between agents’ descriptor functions and other descriptor functions which models the entire mission. The validity of the proposed technique is tested via numerical simulation, using different task assignment scenarios

Approximate dynamic programming with applications in multi-agent systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.MIT Institute Archives copy: contains CDROM of thesis in .pdf format.Includes bibliographical references (p. 151-161).This thesis presents the development and implementation of approximate dynamic programming methods used to manage multi-agent systems. The purpose of this thesis is to develop an architectural framework and theoretical methods that enable an autonomous mission system to manage real-time multi-agent operations. To meet this goal, we begin by discussing aspects of the real-time multi-agent mission problem. Next, we formulate this problem as a Markov Decision Process (MDP) and present a system architecture designed to improve mission-level functional reliability through system self-awareness and adaptive mission planning. Since most multi-agent mission problems are computationally difficult to solve in real-time, approximation techniques are needed to find policies for these large-scale problems. Thus, we have developed theoretical methods used to find feasible solutions to large-scale optimization problems. More specifically, we investigate methods designed to automatically generate an approximation to the cost-to-go function using basis functions for a given MDP. Next, these these techniques are used by an autonomous mission system to manage multi-agent mission scenarios. Simulation results using these methods are provided for a large-scale mission problem. In addition, this thesis presents the implementation of techniques used to manage autonomous unmanned aerial vehicles (UAVs) performing persistent surveillance operations. We present an indoor multi-vehicle testbed called RAVEN (Real-time indoor Autonomous Vehicle test ENvironment) that was developed to study long-duration missions in a controlled environment.(cont.) The RAVEN's design allows researchers to focus on high-level tasks by autonomously managing the platform's realistic air and ground vehicles during multi-vehicle operations, thus promoting the rapid prototyping of UAV technologies by flight testing new vehicle configurations and algorithms without redesigning vehicle hardware. Finally, using the RAVEN, we present flight test results from autonomous, extended mission tests using the technologies developed in this thesis. Flight results from a 24 hr, fully-autonomous air vehicle flight-recharge test and an autonomous, multi-vehicle extended mission test using small, electric-powered air vehicles are provided.by Mario J. Valenti.Ph.D

Aerial collective systems

Deployment of multiple flying robots has attracted the interest of several research groups in the recent times both because such a feat represents many interesting scientific challenges and because aerial collective systems have a huge potential in terms of applications. By working together, multiple robots can perform a given task quicker or more efficiently than a single system. Furthermore, multiple robots can share computing, sensing and communication payloads thus leading to lighter robots that could be safer than a larger system, easier to transport and even disposable in some cases. Deploying a fleet of unmanned aerial vehicles instead of a single aircraft allows rapid coverage of a relatively larger area or volume. Collaborating airborne agents can help each other by relaying communication or by providing navigation means to their neighbours. Flying in formation provides an effective way of decongesting the airspace. Aerial swarms also have an enormous artistic potential because they allow creating physical 3D structures that can dynamically change their shape over time. However, the challenges to actually build and control aerial swarms are numerous. First of all, a flying platform is often more complicated to engineer than a terrestrial robot because of the inherent weight constraints and the absence of mechanical link with any inertial frame that could provide mechanical stability and state reference. In the first section of this chapter, we therefore review this challenges and provide pointers to state-of-the-art methods to solve them. Then as soon as flying robots need to interact with each other, all sorts of problems arise such as wireless communication from and to rapidly moving objects and relative positioning. The aim of section 3 is therefore to review possible approaches to technically enable coordination among flying systems. Finally, section 4 tackles the challenge of designing individual controllers that enable a coherent behavior at the level of the swarm. This challenge is made even more difficult with flying robots because of their 3D nature and their motion constraints that are often related to the specific architectures of the underlying physical platforms. In this third section is complementary to the rest of this book as it focusses only on methods that have been designed for aerial collective systems

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

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Military Aviation: Issues and Options for Combating Terrorism and Counterinsurgency

This report provides background on terrorism and non-state actor challenges, and how military aviation may contribute to operations against these actors. The report discusses issues associated with the use of military aviation against non-state actors, and potential options for consideration

Semi-Autonomous Small Unmanned Aircraft Systems for Sampling Tornadic Supercell Thunderstorms

This work describes the development of a network-centric unmanned aircraft system (UAS) for in situ sampling of supercell thunderstorms. UAS have been identified as a well-suited platform for meteorological observations given their portability, endurance, and ability to mitigate atmospheric disturbances. They represent a unique tool for performing targeted sampling in regions of a supercell thunderstorm previously unreachable through other methods. Doppler radar can provide unique measurements of the wind field in and around supercell thunderstorms. In order to exploit this capability, a planner was developed that can optimize ingress trajectories for severe storm penetration. The resulting trajectories were examined to determine the feasibility of such a mission, and to optimize ingress in terms of flight time and exposure to precipitation. A network-centric architecture was developed to handle the large amount of distributed data produced during a storm sampling mission. Creation of this architecture was performed through a bottom-up design approach which reflects and enhances the interplay between networked communication and autonomous aircraft operation. The advantages of the approach are demonstrated through several field and hardware-in-the-loop experiments containing different hardware, networking protocols, and objectives. Results are provided from field experiments involving the resulting network-centric architecture. An airmass boundary was sampled in the Collaborative Colorado Nebraska Unmanned Aircraft Experiment (CoCoNUE). Utilizing lessons learned from CoCoNUE, a new concept of operations (CONOPS) and UAS were developed to perform in situ sampling of supercell thunderstorms. Deployment during the Verification of the Origins of Rotation in Tornadoes Experiment 2 (VOR- TEX2) resulted in the first ever sampling of the airmass associated with the rear flank downdraft of a tornadic supercell thunderstorm by a UAS. Hardware-in-the-loop simulation capability was added to the UAS to enable further assessment of the system and CONOPS. The simulation combines a full six degree-of-freedom aircraft dynamic model with wind and precipitation data from simulations of severe convective storms. Interfaces were written to involve as much of the system\u27s field hardware as possible, including the creation of a simulated radar product server. A variety of simulations were conducted to evaluate different aspects of the CONOPS used for the 2010 VORTEX2 field campaign

Hybrid Formation Control of Unmanned Helicopters

Ph.DDOCTOR OF PHILOSOPH