Download or read book Optimal and Efficient Geolocation and Path Planning for Unmanned Aerial Vehicles Using Uncertainty Measures written by Sean R. Semper and published by . This book was released on 2011 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: A general frame work for determining an object's absolute position from relative position measurements, commonly called geolocation, is developed in this dissertation. Relative measurements are obtained from a two unmanned aerial vehicle (UAV) team with electronic support measure (ESM) sensors on board. One team combines their time of arrival (TOA) measurements forming one time difference of arrival measurement (TDOA) from an emitter's signal. Using an Extended Kalman Filter (EKF), pseudorange equations containing UAV positions and emitter position estimates are sequentially estimated to solve for absolute emitter positions. Uncertainty metrics are derived for enhancing filter performance, allowing for a theoretical selection of guidance routines given operational requirements. When prior information is present then special stochastic approach is developed to include this information into the guidance routine. When the UAV heading angle contains errors, a newly derived a marginalized adaptive Gaussian sum propagator is used to estimate nonlinear UAV positions. Marginalizing the state-space places computational efforts on the nonlinear portions of the state-space and allows the linear portions to propagated using a linear Kalman Filter (KF). Combining new estimation methods allows one to deal with more complex scenarios and create robust architectures for passive geolocation solutions.

Download or read book Decentralized Geolocation and Optimal Path Planning Using Unmanned Aerial Vehicles written by Sean R. Semper and published by . This book was released on 2008 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: A general frame work for determining an object's absolute position from relative position measurements, commonly called geolocation, is developed in this thesis. Relative measurements are obtained from a two unmanned aerial vehicle (UAV) team with electronic support measure (ESM) sensors on board. One team combines their time of arrival (TOA) measurements forming one time difference of arrival measurement (TDOA) from an emitter's signal. Using an Extended Kalman Filter (EKF), pseudorange equations containing UAV positions and emitter position estimates are sequentially estimated to solve for absolute emitter positions. When N UAV teams are available, a decentralized EKF architecture is derived to optimally fuse estimates from N filters at the global fusion node. In addition, optimal UAV trajectories are developed to minimize the covariance position errors. Weights are placed on the UAV motions, so minimum and maximum distances to the emitting object are restricted.

Download or read book Cooperative Path Planning of Unmanned Aerial Vehicles written by Antonios Tsourdos and published by John Wiley & Sons. This book was released on 2010-11-09 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: An invaluable addition to the literature on UAV guidance and cooperative control, Cooperative Path Planning of Unmanned Aerial Vehicles is a dedicated, practical guide to computational path planning for UAVs. One of the key issues facing future development of UAVs is path planning: it is vital that swarm UAVs/ MAVs can cooperate together in a coordinated manner, obeying a pre-planned course but able to react to their environment by communicating and cooperating. An optimized path is necessary in order to ensure a UAV completes its mission efficiently, safely, and successfully. Focussing on the path planning of multiple UAVs for simultaneous arrival on target, Cooperative Path Planning of Unmanned Aerial Vehicles also offers coverage of path planners that are applicable to land, sea, or space-borne vehicles. Cooperative Path Planning of Unmanned Aerial Vehicles is authored by leading researchers from Cranfield University and provides an authoritative resource for researchers, academics and engineers working in the area of cooperative systems, cooperative control and optimization particularly in the aerospace industry.

Download or read book Robust Trajectory Planning for Unmanned Aerial Vehicles in Uncertain Environments written by Brandon Douglas Luders and published by . This book was released on 2008 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: As unmanned aerial vehicles (UAVs) take on more prominent roles in aerial missions, it becomes necessary to increase the level of autonomy available to them within the mission planner. In order to complete realistic mission scenarios, the UAV must be capable of operating within a complex environment, which may include obstacles and other no-fly zones. Additionally, the UAV must be able to overcome environmental uncertainties such as modeling errors, external disturbances, and an incomplete situational awareness. By utilizing planners which can autonomously navigate within such environments, the cost-effectiveness of UAV missions can be dramatically improved.This thesis develops a UAV trajectory planner to efficiently identify and execute trajectories which are robust to a complex, uncertain environment. This planner, named Efficient RSBK, integrates previous mixed-integer linear programming (MILP) path planning algorithms with several implementation innovations to achieve provably robust on-line trajectory optimization. Using the proposed innovations, the planner is able to design intelligent long-term plans using a minimal number of decision variables. The effectiveness of this planner is demonstrated with both simulation results and flight experiments on a quadrotor testbed.Two major components of the Efficient RSBK framework are the robust model predictive control (RMPC) scheme and the low-level planner. This thesis develops a generalized framework to investigate RMPC affine feedback policies on the disturbance, identify relative strengths and weaknesses, and assess suitability for the UAV trajectory planning problem. A simple example demonstrates that even with a conventional problem setup, the closed-loop performance may not always improve with additional decision variables, despite the resulting increase in computational complexity. A compatible low-level troller is also introduced which significantly improves trajectory-following accuracy, as demonstrated by additional flight experiments.

Download or read book State Estimation and Control for Low cost Unmanned Aerial Vehicles written by Chingiz Hajiyev and published by Springer. This book was released on 2015-06-10 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses state estimation and control procedures for a low-cost unmanned aerial vehicle (UAV). The authors consider the use of robust adaptive Kalman filter algorithms and demonstrate their advantages over the optimal Kalman filter in the context of the difficult and varied environments in which UAVs may be employed. Fault detection and isolation (FDI) and data fusion for UAV air-data systems are also investigated, and control algorithms, including the classical, optimal, and fuzzy controllers, are given for the UAV. The performance of different control methods is investigated and the results compared. State Estimation and Control of Low-Cost Unmanned Aerial Vehicles covers all the important issues for designing a guidance, navigation and control (GNC) system of a low-cost UAV. It proposes significant new approaches that can be exploited by GNC system designers in the future and also reviews the current literature. The state estimation, control and FDI methods are illustrated by examples and MATLAB® simulations. State Estimation and Control of Low-Cost Unmanned Aerial Vehicles will be of interest to both researchers in academia and professional engineers in the aerospace industry. Graduate students may also find it useful, and some sections are suitable for an undergraduate readership.

Download or read book Planning Under Uncertainty for Unmanned Aerial Vehicles written by Ryan Skeele and published by . This book was released on 2016 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned aerial vehicle (UAV) technology has grown out of traditional research and military applications and has captivated the commercial and consumer markets, showing the ability to perform a spectrum of autonomous functions. This technology has the capability of saving lives in search and rescue, fighting wildfires in environmental monitoring, and delivering time dependent medicine in package delivery. These examples demonstrate the potential impact this technology will have on our society. However, it is evident how sensitive UAVs are to the uncertainty of the physical world. In order to properly achieve the full potential of UAVs in these markets, robust and efficient planning algorithms are needed. This thesis addresses the challenge of planning under uncertainty for UAVs. We develop a suite of algorithms that are robust to changes in the environment and build on the key areas of research needed for utilizing UAVs in a commercial setting. Throughout this research three main components emerged: monitoring targets in dynamic environments, exploration with unreliable communication, and risk-aware path planning. We use a realistic fire simulation to test persistent monitoring in an uncertain environment. The fire is generated using the standard program for modeling wildfire, FARSITE. This model was used to validate a weighted-greedy approach to monitoring clustered points of interest (POIs) over traditional methods of tracking a fire front. We implemented the algorithm on a commercial UAV to demonstrate the deployment capability. Dynamic monitoring has limited potential if if coordinated planning is fallible to uncertainty in the world. Uncertain communication can cause critical failures in coordinated planning algorithms. We develop a method for coordinated exploration of a multi-UAV team with unreliable communication and limited battery life. Our results show that the proposed algorithm, which leverages meeting, sacrificing, and relaying behavior, increases the percentage of the environment explored over a frontier-based exploration strategy by up to 18%. We test on teams of up to 8 simulated UAVs and 2 real UAVs able to cope with communication loss and still report improved gains. We demonstrate this work with a pair of custom UAVs in an indoor office environment. We introduce a novel approach to incorporating and addressing uncertainty in planning problems. The proposed Risk-Aware Graph Search (RAGS) algorithm combines traditional deterministic search techniques with risk-aware planning. RAGS is able to trade off the number of future path options, as well as the mean and variance of the associated path cost distributions to make online edge traversal decisions that minimize the risk of executing a high-cost path. The algorithm is compared against existing graphsearch techniques on a set of graphs with randomly assigned edge costs, as well as over a set of graphs with transition costs generated from satellite imagery data. In all cases, RAGS is shown to reduce the probability of executing high-cost paths over A*, D* and a greedy planning approach. High level planning algorithms can be brittle in dynamic conditions where the environment is not modeled perfectly. In developing planners for uncertainty we ensure UAVs will be able to operate in conditions outside the scope of prior techniques. We address the need for robustness in robotic monitoring, coordination, and path planning tasks. Each of the three methods introduced were tested in simulated and real environments, and the results show improvement over traditional algorithms.

Download or read book Autonomous Navigation and Deployment of UAVs for Communication Surveillance and Delivery written by Hailong Huang and published by John Wiley & Sons. This book was released on 2022-09-27 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book UAV Intelligent Path Planning for Wilderness Search and Rescue written by Rongbin Lanny Lin and published by . This book was released on 2009 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: Once a probability distribution map is in place, areas with higher probabilities are searched first in order to find the missing person in the shortest expected time. When using a Unmanned Aerial Vehicle (UAV) to support search, the onboard video camera should cover as much of the important areas as possible within a set time. We explore several algorithms (with and without set destination) and describe some novel techniques in solving this path-planning problem and compare their performances against typical WiSAR scenarios. This problem is NP-hard, but our algorithms yield high quality solutions that approximate the optimal solution, making efficient use of the limited UAV flying time. The capability of planning a path with a set destination also enables the UAV operator to plan a path strategically while letting the UAV plan the path locally.

Download or read book Optimal Path Planning for an Unmanned Aerial Vehicle written by Anand Krishnamurthy Goplan and published by . This book was released on 2005 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Path Planning for Unmanned Aerial Vehicles Using Visibility Line based Methods written by and published by . This book was released on 2011 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book UAV Two dimensional Path Planning in Real time Using Fuzzy Logic written by Chelsea Sabo and published by . This book was released on 2011 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are a variety of scenarios in which the mission objectives rely on a UAV being capable of maneuvering in an environment containing obstacles in which there is little prior knowledge of the surroundings. In these situations, not only can these obstacles be dynamic, but sometimes there is no way to plan ahead of the mission to avoid them. Additionally, there are many situations in which it is desirable to send in an exploratory robot where the environment is dangerous/ contaminated and there is a great deal of uncertainty. These scenarios could either be too risky to send people or not available to humans. With an appropriate dynamic motion planning algorithm in these situations, robots or UAVs would be able to maneuver in any unknown and/or dynamic environment towards a target in real-time. An autonomous system that can handle these varying conditions rapidly and efficiently without failure is imperative to the future of unmanned aerial vehicle (UAV). This paper presents a methodology for two-dimensional path planning of a UAV using fuzzy logic. This approach is selected due to its ability to emulate human decision making and relative ease of implementation. The fuzzy inference system takes information in real time about obstacles (if within the agent's sensing range) and target location and outputs a change in heading angle and speed. The FL controller was validated for both simple (polygon obstacles in a sparse space) and complex environments (i.e. non-polygon obstacles, symmetrical/concave obstacles, dense environments, etc). Additionally, Monte Carlo testing was completed to evaluate the performance of the control method. Not only was the path traversed by the UAV often the exact path computed using an optimal method, the low failure rate makes the Fuzzy Logic Controller (FLC) feasible for exploration. The FLC showed only a total of 3% failure rate, whereas an Artificial Potential Field (APF) solution, a commonly used intelligent control method, had an average of 18% failure rate. Also, the APF method failed about 1/3 of the time for very dense environments (the FLC only had 5% failure rate). These results highlighted one of the advantages of the FLC method: its adaptability to additional rules while maintaining low control effort. Furthermore, the solutions showed superior results when compared to the APF solutions when compared to distance traversed. Overall, the FLC produced solutions that were on average only about 7.7% greater distance traveled (as opposed to 9.7% for the APF).

Download or read book Optimal Algorithm Design for Transfer Path Planning for Unmanned Aerial Vehicles written by Andrew George Pollock and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Path Planning for Unmanned Aerial Vehicles by a Combinatorial Optimization Approach written by and published by . This book was released on 2006 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Unmanned Aerial Vehicles Mission Planning Under Uncertainty written by Philemon Sakamoto and published by . This book was released on 2006 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: (cont.) In this research, we develop a UAV Mission Planner that couples the scheduling of tasks with the assignment of these tasks to UAVs, while maintaining the characteristics of longevity and efficiency in its plans. The planner is formulated as a Mixed Integer Program (MIP) that incorporates the Robust Optimization technique proposed by Bertsimas and Sim [12].

Download or read book Improving Path Planning of Unmanned Aerial Vehicles in an Immersive Environment Using Meta paths and Terrain Information written by Levi Daniel Swartzentruber and published by . This book was released on 2009 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Path Planning for Unmanned Aerial Vehicles Using Visibility Line based Methods written by Rosli Omar and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book UAV Path Planning and Obstacle Avoidance Based on Fuzzy Logic and Kinodynamic RRT Methods written by Long Chen and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Path Planning is one of the important problems to be explored in unmanned aerial vehicle (UAV) to find the optimal path between starting position and destination. The aim of path planning technique is not only to find the shortest path but also to provide the collision-free path for the UAV in unknown environment. Although there have been significant advances on the methods of path planning where the map of environment is known in advance, there are still some challenges to be addressed for dynamic autonomous navigation for the UAV in unknown environment. This thesis research proposes a new path planning method named Fuzzy Kinodynamic RRT for unmanned aerial vehicle flying in the unknown environment. This method generates a global path based on RRT [1] (Rapidly-exploring random tree) and utilizes fuzzy logic system to avoid obstacles in real time. A set of heuristics fuzzy rules are designed to lead the UAV away from unmodeled obstacles and to guide the UAV towards the goal. The rules are also tested in different scenarios, and they are all working efficiently both in simple and complicated cases. The UAV starts to fly along the path generated by RRT, and the fuzzy logic system is then activated when it comes across the obstacle. When the sensor detects no collision within a specific distance, the fuzzy system is turned off and the UAV flies back to the previous path towards the final destination. The simulations of the developed algorithm have been carried out in various scenarios, with the sensor to detect the obstacles. The numerical simulations show the satisfactory results in various scenarios for path planning that considerably reduces the risk of colliding with other stationary and moving obstacles. A more robust and efficient fuzzy logic controller which embeds the path planning is finally proposed and the simulation shows the satisfactory results in complicated environments.