Autonomous Navigation with Obstacle Avoidance for Unmanned Aircraft Systems Using MILP PDF Download

Author: James A. Devens
Publisher:
ISBN:
Category :
Languages : en
Pages : 88

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Book Description
Autonomous coordination among multiple aerial vehicles to ensure a collision free airspace is a critical aspect of today's airspace. With the rise of Unmanned Aerial Vehicles (UAVs) in the military and commercial sectors, obstacle avoidance in a densely populated airspace is necessary. This thesis investigates finding optimal or near-optimal trajectories in real-time for aircraft in complex airspaces containing a large number of obstacles. The solution for the trajectories is described as a linear program subject to mixed integer constraints, known as a Mixed Integer Linear Program (MILP). The resulting MILP problem is solved in real time using a well-known, public domain MILP solver. In addition, an Exhaustive, Breadth-First Search algorithm was implemented and is used for comparison in terms of execution time and flight path optimality. The Exhaustive Search algorithm is comprised of a multi-branch tree structure that iterates through all possible flight paths from source to target. The MILP solution was implemented in both PC based and embedded system environments. The embedded system environment was implemented on an onboard processor to develop trajectories for each individual aircraft in real time.

Author: Umberto Papa
Publisher: Mdpi AG
ISBN: 9783036580524
Category : Science
Languages : en
Pages : 0

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Book Description
The aim of this book is to seek high-quality contributions that highlight novel research results and emerging applications, addressing recent breakthroughs in UAS autonomous navigation and related fields, such as flight mechanics and control, structural design, sensor design, etc. The topics of interest include the following: two-dimensional and three-dimensional mapping, target detection, and obstacle avoidance; the active perception of targets in cluttered environments (foliage, forests, etc.); vision-based and optical flow techniques; sensors and sensor fusion techniques; design models for guidance and controlled flight; state estimation, data analysis and filtering techniques (KF, EKF, particle filtering, fuzzy logic, etc.); path planning and path management; optimal control and strategies (neural networks, fuzzy logic, reinforcement learning, evolutionary and genetic algorithms, AI, etc.); navigation in GPS-denied environments; autolanding and safe landing area definition (SLAD); environmental effects on UAVs (wind, etc.); autonomous UAV or MAV swarms, and distributed architectures; BVLOS autonomous navigation.

Author: Yunior I. Cruz
Publisher:
ISBN:
Category : Aircraft separation
Languages : en
Pages : 37

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Book Description
The level of human interaction with Unmanned Aerial Systems varies greatly from remotely piloted aircraft to fully autonomous systems. In the latter end of the spectrum, the challenge lies in designing effective algorithms to dictate the behavior of the autonomous agents. A swarm of autonomous Unmanned Aerial Vehicles requires collision avoidance and formation flight algorithms to negotiate environmental challenges it may encounter during the execution of its mission, which may include obstacles and chokepoints. In this work, a simple algorithm is developed to allow a formation of autonomous vehicles to perform point to point navigation while avoiding obstacles and navigating through chokepoints. Emphasis is placed on maintaining formation structures. Rather than breaking formation and individually navigating around the obstacle or through the chokepoint, vehicles are required to assemble into appropriately sized/shaped sub-formations, bifurcate around the obstacle or negotiate the chokepoint, and reassemble into the original formation at the far side of the obstruction. The algorithm receives vehicle and environmental properties as inputs and outputs trajectories for each vehicle from start to the desired ending location. Simulation results show that the algorithm safely routes all vehicles past the obstruction while adhering to the aforementioned requirements. The formation adapts and successfully negotiates the obstacles and chokepoints in its path while maintaining proper vehicle separation.

Author: Pedro Castillo-Garcia
Publisher: Butterworth-Heinemann
ISBN: 0128053399
Category : Technology & Engineering
Languages : en
Pages : 302

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Book Description
Indoor Navigation Strategies for Aerial Autonomous Systems presents the necessary and sufficient theoretical basis for those interested in working in unmanned aerial vehicles, providing three different approaches to mathematically represent the dynamics of an aerial vehicle. The book contains detailed information on fusion inertial measurements for orientation stabilization and its validation in flight tests, also proposing substantial theoretical and practical validation for improving the dropped or noised signals. In addition, the book contains different strategies to control and navigate aerial systems. The comprehensive information will be of interest to both researchers and practitioners working in automatic control, mechatronics, robotics, and UAVs, helping them improve research and motivating them to build a test-bed for future projects. - Provides substantial information on nonlinear control approaches and their validation in flight tests - Details in observer-delay schemes that can be applied in real-time - Teaches how an IMU is built and how they can improve the performance of their system when applying observers or predictors - Improves prototypes with tactics for proposed nonlinear schemes

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 13

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Book Description
The US Navy and other Department of Defense (DoD) and Department of Homeland Security (DHS) organizations are increasingly interested in the use of unmanned surface vehicles (USVs) for a variety of missions and applications. In order for USVs to fill these roles, they must be capable of a relatively high degree of autonomous navigation. Space and Naval Warfare Systems Center, San Diego is developing core technologies required for robust USV operation in a real-world environment, primarily focusing on autonomous navigation, obstacle avoidance, and path planning.

Author: Hailong Huang
Publisher: John Wiley & Sons
ISBN: 1119870836
Category : Technology & Engineering
Languages : en
Pages : 276

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Book Description
Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery Authoritative resource offering coverage of communication, surveillance, and delivery problems for teams of unmanned aerial vehicles (UAVs) Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery studies various elements of deployment of networks of unmanned aerial vehicle (UAV) base stations for providing communication to ground users in disaster areas, covering problems like ground traffic monitoring, surveillance of environmental disaster areas (e.g. brush fires), using UAVs in rescue missions, converting UAV video surveillance, and more. The work combines practical problems, implementable and computationally efficient algorithms to solve these problems, and mathematically rigorous proofs of each algorithm’s convergence and performance. One such example provided by the authors is a novel biologically inspired motion camouflage algorithm to covert video surveillance of moving targets by an unmanned aerial vehicle (UAV). All autonomous navigation and deployment algorithms developed in the book are computationally efficient, easily implementable in engineering practice, and based only on limited information on other UAVs of each and the environment. Sample topics discussed in the work include: Deployment of UAV base stations for communication, especially with regards to maximizing coverage and minimizing interference Deployment of UAVs for surveillance of ground areas and targets, including surveillance of both flat and uneven areas Navigation of UAVs for surveillance of moving areas and targets, including disaster areas and ground traffic monitoring Autonomous UAV navigation for covert video surveillance, offering extensive coverage of optimization-based navigation Integration of UAVs and public transportation vehicles for parcel delivery, covering both one-way and round trips Professionals in navigation and deployment of unmanned aerial vehicles, along with researchers, engineers, scientists in intersecting fields, can use Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery to gain general knowledge on the subject along with practical, precise, and proven algorithms that can be deployed in a myriad of practical situations.

Author: Keeryun Kang
Publisher:
ISBN:
Category : Drone aircraft
Languages : en
Pages :

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Book Description
This thesis presents an integrated framework for online obstacle avoidance of rotary-wing unmanned aerial vehicles (UAVs), which can provide UAVs an obstacle field navigation capability in a partially or completely unknown obstacle-rich environment. The framework is composed of a LIDAR interface, a local obstacle grid generation, a receding horizon (RH) trajectory optimizer, a global shortest path search algorithm, and a climb rate limit detection logic. The key feature of the framework is the use of an optimization-based trajectory generation in which the obstacle avoidance problem is formulated as a nonlinear trajectory optimization problem with state and input constraints over the finite range of the sensor. This local trajectory optimization is combined with a global path search algorithm which provides a useful initial guess to the nonlinear optimization solver. Optimization is the natural process of finding the best trajectory that is dynamically feasible, safe within the vehicle's flight envelope, and collision-free at the same time. The optimal trajectory is continuously updated in real time by the numerical optimization solver, Nonlinear Trajectory Generation (NTG), which is a direct solver based on the spline approximation of trajectory for dynamically flat systems. In fact, the overall approach of this thesis to finding the optimal trajectory is similar to the model predictive control (MPC) or the receding horizon control (RHC), except that this thesis followed a two-layer design; thus, the optimal solution works as a guidance command to be followed by the controller of the vehicle. The framework is implemented in a real-time simulation environment, the Georgia Tech UAV Simulation Tool (GUST), and integrated in the onboard software of the rotary-wing UAV test-bed at Georgia Tech. Initially, the 2D vertical avoidance capability of real obstacles was tested in flight. Then the flight test evaluations were extended to the benchmark tests for 3D avoidance capability over the virtual obstacles, and finally it was demonstrated on real obstacles located at the McKenna MOUT site in Fort Benning, Georgia. Simulations and flight test evaluations demonstrate the feasibility of the developed framework for UAV applications involving low-altitude flight in an urban area.

Author: Kenzo Nonami
Publisher: Springer Science & Business Media
ISBN: 4431538569
Category : Technology & Engineering
Languages : en
Pages : 341

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Book Description
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.

Author: Andrey V. Savkin
Publisher: Butterworth-Heinemann
ISBN: 0128037571
Category : Technology & Engineering
Languages : en
Pages : 360

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Book Description
Safe Robot Navigation Among Moving and Steady Obstacles is the first book to focus on reactive navigation algorithms in unknown dynamic environments with moving and steady obstacles. The first three chapters provide introduction and background on sliding mode control theory, sensor models, and vehicle kinematics. Chapter 4 deals with the problem of optimal navigation in the presence of obstacles. Chapter 5 discusses the problem of reactively navigating. In Chapter 6, border patrolling algorithms are applied to a more general problem of reactively navigating. A method for guidance of a Dubins-like mobile robot is presented in Chapter 7. Chapter 8 introduces and studies a simple biologically-inspired strategy for navigation a Dubins-car. Chapter 9 deals with a hard scenario where the environment of operation is cluttered with obstacles that may undergo arbitrary motions, including rotations and deformations. Chapter 10 presents a novel reactive algorithm for collision free navigation of a nonholonomic robot in unknown complex dynamic environments with moving obstacles. Chapter 11 introduces and examines a novel purely reactive algorithm to navigate a planar mobile robot in densely cluttered environments with unpredictably moving and deforming obstacles. Chapter 12 considers a multiple robot scenario. For the Control and Automation Engineer, this book offers accessible and precise development of important mathematical models and results. All the presented results have mathematically rigorous proofs. On the other hand, the Engineer in Industry can benefit by the experiments with real robots such as Pioneer robots, autonomous wheelchairs and autonomous mobile hospital. - First book on collision free reactive robot navigation in unknown dynamic environments - Bridges the gap between mathematical model and practical algorithms - Presents implementable and computationally efficient algorithms of robot navigation - Includes mathematically rigorous proofs of their convergence - A detailed review of existing reactive navigation algorithm for obstacle avoidance - Describes fundamentals of sliding mode control

Author: Laird-Philip Ryan Lewis
Publisher:
ISBN:
Category : Engineering
Languages : en
Pages : 161

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Book Description
This work introduces the use of optimal control methods for path planning and control of autonomous vehicles in an obstacle-rich environment. Traditional techniques harbor non-optimal, closed architectures primarily derived at a time when computational complexity could significantly hinder overall system performance. Advancements in computing power, miniaturization, and numerical methods permit the utilization of online, optimal path planning and control, thereby improving system flexibility and autonomy. The backbone of this concept is state-of-the-art optimal control techniques involving pseudospectral methods and sequential quadratic programming. Although this research focuses on a robotic car or Unmanned Ground Vehicle (UGV), several systems, including an Unmanned Aerial Vehicle (UAV) and a pendulum on a rotational base, are detailed for the purpose of illustrating the technique's modularity. With respect to the UGV, optimal control methods permit the optimization of maneuver parameters while accounting for complex vehicle kinematics and workspace obstacles, represented as dynamic and path constraints respectively. The path constraints are modeled such that an obstacle of any shape or size can be included. Maneuvering trajectories are first generated in an open-loop architecture, followed by an application of these same techniques in feedback form. Lastly, model fidelity is increased to improve control over vehicle behavior and closed-loop performance and a local knowledge scenario is evaluated.