Download or read book Robust Planning for Heterogeneous Unmanned Aerial Vehicles in Uncertain Environments written by Luca Francesco Bertuccelli and published by . This book was released on 2004 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: (Cont.) of the strike mission. The design and development of a new addition to a heterogeneous vehicle testbed is also presented.

Download or read book Robust Multi unmanned Aerial Vehicles Planning in Dynamic and Uncertain Environments written by Chung Tin and published by . This book was released on 2004 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: Future unmanned aerial vehicles (UAVs) are expected to operate with higher level of autonomy to execute very complex military and civilian applications. New methods in planning and execution are required to coordinate these vehicles in real-time to ensure maximal efficiency of the team activities. These algorithms must be fast to enable rapid replanning in a dynamic environment. The planner must also be robust to uncertainty in the situational awareness. This thesis investigates the impact of information uncertainty and environmental changes to the task assignment and path planning algorithms. Several new techniques are presented that both speed up and embed robustness into previously published algorithms. The first is an incremental algorithm that significantly reduces the time required to update the cost map used in the task assignment when small changes occur in a complex environment. The second introduces a new robust shortest path algorithm that accounts for uncertainty in the arc costs. The algorithm is computational tractable and is shown to yield performance and robustness that are comparable to more sophisticated algorithms that are not suitable for real-time implementation. Experimental results are presented using this technique on a rover testbed. This thesis also extends a UAV search algorithm to include moving targets in the environment. This new algorithm coordinates a team of UAVs to search an unknown environment while balancing the need to track moving targets. These three improvements have had a big impact because they modify the Receding Horizon Mixed-Integer Linear Programming (RH-MILP) control hierarchy to handle uncertainty and properly react to rapid changes in the environment. Hence, these improvements enable the RH-MILP controller to be implemented in more realistic scenarios.

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 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 Multiple Heterogeneous Unmanned Aerial Vehicles written by Aníbal Ollero and published by Springer. This book was released on 2007-10-25 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complete with online files and updates, this cutting-edge text looks at the next generation of unmanned flying machines. Aerial robots can be considered as an evolution of the Unmanned Aerial Vehicles (UAVs). This book provides a complete overview of all the issues related to aerial robotics, addressing problems ranging from flight control to terrain perception and mission planning and execution. The major challenges and potentials of heterogeneous UAVs are comprehensively explored.

Download or read book Robust Planning for Effects Based Operations written by Corban Harrell Bryant and published by . This book was released on 2006 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: (cont.) We demonstrate how robust planning increases the length of time that a plan remains feasible in execution and achieves better overall value by avoiding re-planning costs. We analyze strengths and weaknesses of each model and suggest when their use is appropriate. Finally, we apply Hlinan Machine Collaborative Decision Making (HMICDM) concepts to propose methods to facilitate human interaction with a robust effects-based planner.

Download or read book Robust Formation Control for Multiple Unmanned Aerial Vehicles written by Hao Liu and published by CRC Press. This book was released on 2022-12-01 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on the authors’ recent research results on formation control problems, including time-varying formation, communication delays, fault-tolerant formation for multiple UAV systems with highly nonlinear and coupled, parameter uncertainties, and external disturbances. Differentiating from existing works, this book presents a robust optimal formation approach to designing distributed cooperative control laws for a group of UAVs, based on the linear quadratic regulator control method and the robust compensation theory. The proposed control method is composed of two parts: the nominal part to achieve desired tracking performance and the robust compensation part to restrain the influence of highly nonlinear and strongly coupled parameter uncertainties, and external disturbances on the global closed-loop control system. Furthermore, this book gives proof of their robust properties. The influence of communication delays and actuator fault tolerance can be restrained by the proposed robust formation control protocol, and the formation tracking errors can converge into a neighborhood of the origin bounded by a given constant in a finite time. Moreover, the book provides details about the practical application of the proposed method to design formation control systems for multiple quadrotors and tail-sitters. Additional features include a robust control method that is proposed to address the formation control problem for UAVs and theoretical and experimental research for the cooperative flight of the quadrotor UAV group and the tail-sitter UAV group. Robust Formation Control for Multiple Unmanned Aerial Vehicles is suitable for graduate students, researchers, and engineers in the system and control community, especially those engaged in the areas of robust control, UAV swarming, and multi-agent systems.

Download or read book Examination of Planning Under Uncertainty Algorithms for Cooperative Unmanned Aerial Vehicles written by Rikin Bharat Gandhi and published by . This book was released on 2005 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: (Cont.) of UAVs and targets. Additionally, sensitivity trials are used to capture each algorithm's robustness to real world planning environments where planners must negotiate incomplete or inaccurate system models. The mission performances of both methods degrade as the quality of their system models worsen.

Download or read book Robust Distributed Planning Strategies for Autonomous Multi agent Teams written by Sameera S. Ponda and published by . This book was released on 2012 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increased use of autonomous robotic agents, such as unmanned aerial vehicles (UAVs) and ground rovers, for complex missions has motivated the development of autonomous task allocation and planning methods that ensure spatial and temporal coordination for teams of cooperating agents. The basic problem can be formulated as a combinatorial optimization (mixed-integer program) involving nonlinear and time-varying system dynamics. For most problems of interest, optimal solution methods are computationally intractable (NP-Hard), and centralized planning approaches, which usually require high bandwidth connections with a ground station (e.g. to transmit received sensor data, and to dispense agent plans), are resource intensive and react slowly to local changes in dynamic environments. Distributed approximate algorithms, where agents plan individually and coordinate with each other locally through consensus protocols, can alleviate many of these issues and have been successfully used to develop real-time conflict-free solutions for heterogeneous networked teams. An important issue associated with autonomous planning is that many of the algorithms rely on underlying system models and parameters which are often subject to uncertainty. This uncertainty can result from many sources including: inaccurate modeling due to simplifications, assumptions, and/or parameter errors; fundamentally nondeterministic processes (e.g. sensor readings, stochastic dynamics); and dynamic local information changes. As discrepancies between the planner models and the actual system dynamics increase, mission performance typically degrades. The impact of these discrepancies on the overall quality of the plan is usually hard to quantify in advance due to nonlinear effects, coupling between tasks and agents, and interdependencies between system constraints. However, if uncertainty models of planning parameters are available, they can be leveraged to create robust plans that explicitly hedge against the inherent uncertainty given allowable risk thresholds. This thesis presents real-time robust distributed planning strategies that can be used to plan for multi-agent networked teams operating in stochastic and dynamic environments. One class of distributed combinatorial planning algorithms involves using auction algorithms augmented with consensus protocols to allocate tasks amongst a team of agents while resolving conflicting assignments locally between the agents. A particular algorithm in this class is the Consensus-Based Bundle Algorithm (CBBA), a distributed auction protocol that guarantees conflict-free solutions despite inconsistencies in situational awareness across the team. CBBA runs in polynomial time, demonstrating good scalability with increasing numbers of agents and tasks. This thesis builds upon the CBBA framework to address many realistic considerations associated with planning for networked teams, including time-critical mission constraints, limited communication between agents, and stochastic operating environments. A particular focus of this work is a robust extension to CBBA that handles distributed planning in stochastic environments given probabilistic parameter models and different stochastic metrics. The Robust CBBA algorithm proposed in this thesis provides a distributed real-time framework which can leverage different stochastic metrics to hedge against parameter uncertainty. In mission scenarios where low probability of failure is required, a chance-constrained stochastic metric can be used to provide probabilistic guarantees on achievable mission performance given allowable risk thresholds. This thesis proposes a distributed chance-constrained approximation that can be used within the Robust CBBA framework, and derives constraints on individual risk allocations to guarantee equivalence between the centralized chance-constrained optimization and the distributed approximation. Different risk allocation strategies for homogeneous and heterogeneous teams are proposed that approximate the agent and mission score distributions a priori, and results are provided showing improved performance in time-critical mission scenarios given allowable risk thresholds.

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 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 Unmanned Aerial Systems written by Anis Koubaa and published by Academic Press. This book was released on 2021-01-21 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned Aerial Systems: Theoretical Foundation and Applications presents some of the latest innovative approaches to drones from the point-of-view of dynamic modeling, system analysis, optimization, control, communications, 3D-mapping, search and rescue, surveillance, farmland and construction monitoring, and more. With the emergence of low-cost UAS, a vast array of research works in academia and products in the industrial sectors have evolved. The book covers the safe operation of UAS, including, but not limited to, fundamental design, mission and path planning, control theory, computer vision, artificial intelligence, applications requirements, and more. This book provides a unique reference of the state-of-the-art research and development of unmanned aerial systems, making it an essential resource for researchers, instructors and practitioners. - Covers some of the most innovative approaches to drones - Provides the latest state-of-the-art research and development surrounding unmanned aerial systems - Presents a comprehensive reference on unmanned aerial systems, with a focus on cutting-edge technologies and recent research trends in the area

Download or read book Robot Manipulator Control written by Frank L. Lewis and published by CRC Press. This book was released on 2003-12-12 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robot Manipulator Control offers a complete survey of control systems for serial-link robot arms and acknowledges how robotic device performance hinges upon a well-developed control system. Containing over 750 essential equations, this thoroughly up-to-date Second Edition, the book explicates theoretical and mathematical requisites for controls design and summarizes current techniques in computer simulation and implementation of controllers. It also addresses procedures and issues in computed-torque, robust, adaptive, neural network, and force control. New chapters relay practical information on commercial robot manipulators and devices and cutting-edge methods in neural network control.

Download or read book Robust and Agile UAV Mission Planning written by Lanah Evers and published by . This book was released on 2013 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Robust Planning for Unmanned Underwater Vehicles written by Emily Anne Frost and published by . This book was released on 2013 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, I design and implement a novel method of schedule and path selection between predetermined waypoints for unmanned underwater vehicles under uncertainty. The problem is first formulated as a mixed-integer optimization model and subsequently uncertainty is addressed using a robust optimization approach. Solutions were tested through simulation and computational results are presented which indicate that the robust approach handles larger problems than could previously be solved in a reasonable running time while preserving a high level of robustness. This thesis demonstrates that the robust methods presented can solve realistic-sized problems in reasonable runtimes - a median of ten minutes and a mean of thirty minutes for 32 tasks - and that the methods perform well both in terms of expected reward and robustness to disturbances in the environment. The latter two results are obtained by simulating solutions given by the deterministic method, a naive robust method, and finally the two restricted affine robust policies. The two restricted affine policies consistently show an expected reward of nearly 100%, while the deterministic and naive robust methods achieve approximately 50% of maximum reward possible.

Download or read book Multi UAV Planning and Task Allocation written by Yasmina Bestaoui Sebbane and published by CRC Press. This book was released on 2020-03-27 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-robot systems are a major research topic in robotics. Designing, testing, and deploying aerial robots in the real world is a possibility due to recent technological advances. This book explores different aspects of cooperation in multiagent systems. It covers the team approach as well as deterministic decision-making. It also presents distributed receding horizon control, as well as conflict resolution, artificial potentials, and symbolic planning. The book also covers association with limited communications, as well as genetic algorithms and game theory reasoning. Multiagent decision-making and algorithms for optimal planning are also covered along with case studies. Key features: Provides a comprehensive introduction to multi-robot systems planning and task allocation Explores multi-robot aerial planning; flight planning; orienteering and coverage; and deployment, patrolling, and foraging Includes real-world case studies Treats different aspects of cooperation in multiagent systems Both scientists and practitioners in the field of robotics will find this text valuable.

Download or read book Advances in Unmanned Aerial Vehicles written by Kimon P. Valavanis and published by Springer Science & Business Media. This book was released on 2008-02-26 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decade has seen tremendous interest in the production and refinement of unmanned aerial vehicles, both fixed-wing, such as airplanes and rotary-wing, such as helicopters and vertical takeoff and landing vehicles. This book provides a diversified survey of research and development on small and miniature unmanned aerial vehicles of both fixed and rotary wing designs. From historical background to proposed new applications, this is the most comprehensive reference yet.