Download or read book Trajectory Planning for Flights in Multiagent and Dynamic Environments written by Jesus Tordesillas Torres and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: While efficient and fast trajectory planners in static worlds have been extensively proposed for UAVs (Unmanned Aerial Vehicles), a 3D real-time planner for environments with static obstacles, dynamic obstacles, and other planning agents still remains an open problem. The dynamic nature of these environments demands high replanning rates, making this problem especially hard on computationally limited platforms. Existing state-of-the-art planners reduce the computational complexity at the expense of more conservative results by relying on three main simplifications or assumptions: First, the collision avoidance constraints are imposed using the Bernstein and B-Spline polynomial bases, which do not tightly enclose a given interval of a polynomial trajectory. Second, multiagent planners usually make centralized and/or synchronized computation assumptions, which lead to poor scalability with the number of agents or can degrade the overall performance. Finally, position and yaw are decoupled when optimizing perception-aware trajectories, which produces highly conservative results. This thesis addresses the aforementioned limitations with the following contributions: First, it presents the MINVO basis, a polynomial basis that generates the simplex with minimum volume enclosing a polynomial curve, therefore reducing the conservativeness in the obstacle avoidance constraints. Leveraging the MINVO basis, this thesis then proposes a tractable way to avoid dynamic obstacles by imposing linear separability constraints between the polyhedral enclosures of the intervals of the trajectories. This is then extended to multiagent scenarios, and a decentralized and asynchronous obstacle avoidance algorithm among many replanning agents is presented. Real-time perception-aware planning is achieved by implicitly imposing the underactuated dynamics of the UAV through the Hopf fibration while jointly optimizing the full pose. Finally, a reduction of two orders of magnitude in the computation time is obtained by learning a policy that imitates the optimization-based planner. These proposed contributions are extensively evaluated in simulation, showing up to 32 agents planning in real time, and in real-world experiments, showcasing flights up to 5.8 m/s in unknown dynamic environments with only onboard computation.

Download or read book Decentralized Multiagent Trajectory Planning in Real world Environments written by Kota Kondo and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the rapidly evolving domain of unmanned aerial vehicle (UAV) applications, multiagent trajectory planning plays an indispensable role. The applications encompass search and rescue missions, surveillance, package delivery, and more. Each of these scenarios necessitates intricate coordination amongst multiple UAVs, driving the need for sophisticated multiagent trajectory planning. Although many centralized trajectory planners exist, they hinge on a single entity for trajectory planning, making them less scalable and challenging to deploy in real-world environments. To address this hurdle, the focus has shifted towards decentralized multiagent trajectory planners, where each agent independently plans its trajectory. In this thesis, we introduce two novel approaches --Robust MADER (RMADER) and PRIMER, aiming at further advancing the field of decentralized multiagent trajectory planning for UAVs. One of the primary hurdles in achieving a multiagent trajectory planner lies in the development of a system that is both scalable and robust, and can be effectively deployed in real-world environments. These environments present numerous challenges, including communication delays and dynamically moving obstacles. To counter these hurdles, we propose RMADER, a decentralized, asynchronous multiagent trajectory planner. RMADER is designed to be robust to communication delays by introducing (1) a delay check step and (2) a two-step trajectory-sharing scheme. RMADER guarantees safety by always keeping a collision-free trajectory and performing a delay check step, even under communication delay. To evaluate RMADER, we performed extensive benchmark studies against state-of-the-art trajectory planners and flight experiments using a decentralized communication architecture called a mesh network with multiple UAVs in dynamic environments. The results demonstrate RMADER's robustness and capability to carry out collision avoidance in dynamic environments, outperforming existing state-of-the-art methods with a 100% collision-free success rate. While RMADER achieves highly scalable and robust multiagent trajectory planning, it requires agents to communicate to share their future trajectories. However, due to localization errors/uncertainties, trajectory deconfliction can fail even if trajectories are perfectly shared between agents. To address this issue, we first present PARM and PARM*, perception-aware, decentralized, asynchronous multiagent trajectory planners that enable a team of agents to navigate uncertain environments while deconflicting trajectories and avoiding obstacles using perception information. PARM* differs from PARM as it is less conservative, using more variables to find closer-to-optimal solutions. Though these methods achieve state-of-the-art performance, they suffer from high computational costs as they need to solve large optimization problems onboard, making it difficult for agents to replan at high rates. To overcome this challenge, we present PRIMER, a learning-based planner trained with imitation learning (IL) using PARM* as the expert demonstrator. PRIMER leverages the low computational requirements at deployment of neural networks and achieves much faster computation speed than optimization-based approaches. In summary, this thesis puts forth RMADER and PRIMER as innovative solutions in the realm of decentralized multiagent trajectory planning, enhancing scalability, robustness, and deployability in real-world UAV applications.

Download or read book Trajectory Planner for Agile Flights in Unknown Environments written by Jesús Tordesillas Torres and published by . This book was released on 2019 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: Planning high-speed trajectories for UAVs in unknown environments requires extremely fast algorithms able to solve the trajectory generation problem in real-time in order to be able to react quickly to the changing knowledge of the world and that guarantee safety at all times. In this thesis, we first show the computational intractability of solving the planning problem by using the full nonlinear dynamics of the UAV in a complex cluttered known environment. By making use of the differential flatness of the UAV and removing the assumption of a completely known world, we then use a convex decomposition of the space and reformulate the optimization problem of the local planner as a Mixed Integer Quadratic Program (MIQP). The formulation proposed enables the solver to choose the interval allocation (i.e. which interval of the trajectory belongs to which polytope), and the time allocation is computed efficiently using the results of the previous replanning iteration. We also address the erratic or unstable behavior that usually appears when a hierarchical planning architecture (a slow, low-fidelity global planner guiding a fast, high-fidelity local planner) is adopted. This is a consequence of not capturing higher-order dynamics in the global planner, whose solution is changing constantly. We therefore propose a way to address this interaction, taking into account the dynamics of the UAV to reduce the discrepancy between the local and global planner. Moreover, safety guarantees are usually obtained by having a local planner that plans a trajectory with a final "stop" condition in the free-known space. However, this decision typically leads to slow and conservative trajectories. We propose a way to obtain faster trajectories by enabling the local planner to optimize in both free-known and unknown spaces. Safety guarantees are ensured by always having a feasible, safe back-up trajectory in the free-known space at the start of each replanning step. The planning framework proposed (called FASTER - FAst and Safe Trajectory PlannER) is validated extensively in simulation and hardware experiments, showing replanning times of 20-65 ms in cluttered environments, with vehicle's speeds up to 7.8 m/s.

Download or read book Advances in Guidance Navigation and Control written by Liang Yan and published by Springer Nature. This book was released on 2023-02-10 with total page 7455 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features the latest theoretical results and techniques in the field of guidance, navigation, and control (GNC) of vehicles and aircrafts. It covers a wide range of topics, including but not limited to, intelligent computing communication and control; new methods of navigation, estimation and tracking; control of multiple moving objects; manned and autonomous unmanned systems; guidance, navigation and control of miniature aircraft; and sensor systems for guidance, navigation and control etc. Presenting recent advances in the form of illustrations, tables, and text, it also provides detailed information of a number of the studies, to offer readers insights for their own research. In addition, the book addresses fundamental concepts and studies in the development of GNC, making it a valuable resource for both beginners and researchers wanting to further their understanding of guidance, navigation, and control.

Download or read book Motion Planning in Dynamic Environments written by Kikuo Fujimura and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Science Workbench is a monograph series which will provide you with an in-depth working knowledge of current developments in computer technology. Every volume in this series will deal with a topic of importance in computer science and elaborate on how you yourself can build systems related to the main theme. You will be able to develop a variety of systems, including computer software tools, computer graphics, computer animation, database management systems, and computer-aided design and manufacturing systems. Computer Science Workbench represents an important new contribution in the field of practical computer technology. TOSIYASU L. KUNII To my parents Kenjiro and Nori Fujimura Preface Motion planning is an area in robotics that has received much attention recently. Much of the past research focuses on static environments - various methods have been developed and their characteristics have been well investigated. Although it is essential for autonomous intelligent robots to be able to navigate within dynamic worlds, the problem of motion planning in dynamic domains is relatively little understood compared with static problems.

Download or read book Nature Inspired Computation in Navigation and Routing Problems written by Xin-She Yang and published by Springer Nature. This book was released on 2020-02-19 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses all the major nature-inspired algorithms with a focus on their application in the context of solving navigation and routing problems. It also reviews the approximation methods and recent nature-inspired approaches for practical navigation, and compares these methods with traditional algorithms to validate the approach for the case studies discussed. Further, it examines the design of alternative solutions using nature-inspired techniques, and explores the challenges of navigation and routing problems and nature-inspired metaheuristic approaches.

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Real Time Trajectory Generation for Autonomous Nonlinear Flight Systems written by and published by . This book was released on 2006 with total page 67 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned aerial vehicle and smart munition systems need robust, real-time path generation and guidance systems to avoid terrain obstructions, navigate in hazardous weather conditions, and react to mobile threats such as radar, jammers, and unfriendly aircraft. In Phase 1 of this STTR project, real-time path planning and trajectory generation techniques for two dimensional flight were developed and demonstrated in software simulation. In Phase 2 these algorithms were refined, extended and were demonstrated in flight on a unique low-cost micro-air vehicle with a payload which included three optical flow sensors, a laser ranger, and a video camera. This report is a comprehensive technical summary of the significant work completed in Phase 2 to enable development of autonomous flight control systems which are capable of accomplishing the complex task of path and trajectory planning in dynamic and uncertain environments.

Download or read book Real time Trajectory Planning for Ground and Aerial Vehicles in a Dynamic Environment written by Jian Yang and published by . This book was released on 2008 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, a novel and generic solution of trajectory generation is developed and evaluated for ground and aerial vehicles in a dynamic environment. By explicitly considering a kinematic model of the ground vehicles, the family of feasible trajectories and their corresponding steering controls are derived in a closed form and are expressed in terms of one adjustable parameter for the purpose of collision avoidance. A collision-avoidance condition is developed for the dynamically changing environment, which consists of a time criterion and a geometrical criterion. By imposing this condition, one can determine a family of collision-free paths in a closed form. Then, optimization problems with respect to different performance indices are setup to obtain optimal solutions from the feasible trajectories. Among these solutions, one with respect to the near-shortest distance and another with respect to the near-minimal control energy are analytical and simple. These properties make them good choices for real-time trajectory planning. Such optimal paths meet all boundary conditions, are twice differentiable, and can be updated in real time once a change in the environment is detected. Then this novel method is extended to 3D space to find a real-time optimal path for aerial vehicles. After that, to reflect the real applications, obstacles are classified to two types: "hard" obstacles that must be avoided, and "soft" obstacles that can be run over/through. Moreover, without losing generality, avoidance criteria are extended to obstacles with any geometric shapes. This dissertation also points out that the emphases of the future work are to consider other constraints such as the bounded velocity and so on. The proposed method is illustrated by computer simulations.

Download or read book Robust Randomized Trajectory Planning for Satellite Attitude Tracking Control written by Drew Richard Barker and published by . This book was released on 2006 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis presents a novel guidance strategy that uses a randomized trajectory planning algorithm in a closed-loop fashion to provide robust motion planning and execution. By closing the guidance, navigation, and control loop around a randomized trajectory planning algorithm, a robotic vehicle can autonomously maneuver through a field of moving obstacles in a robust manner. The guidance strategy provides executable plans that are robust to known error sources when supplied with an estimate of the initial state, the goal, the predicted locations of obstacles, and bounds on error sources affecting the execution of a planned trajectory. The planning function presented in this thesis extends the Rapidly-exploring Random Tree algorithm to dynamic environments by exploring the configuration- x-time space using a node selection metric based on the maneuvering capability of the vehicle. The guidance strategy and the new randomized trajectory planning algorithm are applied to a challenging satellite attitude guidance problem in simulation.

Download or read book Multi scale Path Planning for Reduced Environmental Impact of Aviation written by Scot E. Campbell and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A future air traffic management system capable of rerouting aircraft trajectories in real-time in response to transient and evolving events would result in increased aircraft efficiency, better utilization of the airspace, and decreased environmental impact. Mixed-integer linear programming (MILP) is used within a receding horizon framework to form aircraft trajectories which mitigate persistent contrail formation, avoid areas of convective weather, and seek a minimum fuel solution. Areas conducive to persistent contrail formation and areas of convective weather occur at disparate temporal and spatial scales, and thereby require the receding horizon controller to be adaptable to multi-scale events. In response, a novel adaptable receding horizon controller was developed to account for multi-scale disturbances, as well as generate trajectories using both a penalty function approach for obstacle penetration and hard obstacle avoidance constraints. A realistic aircraft fuel burn model based on aircraft data and engine performance simulations is used to form the cost function in the MILP optimization. The performance of the receding horizon algorithm is tested through simulation. A scalability analysis of the algorithm is conducted to ensure the tractability of the path planner. The adaptable receding horizon algorithm is shown to successfully negotiate multi-scale environments with performance exceeding static receding horizon solutions. The path planner is applied to realistic scenarios involving real atmospheric data. A single flight example for persistent contrail mitigation shows that fuel burn increases 1.48% when approximately 50% of persistent contrails are avoided, but 6.19% when 100% of persistent contrails are avoided. Persistent contrail mitigating trajectories are generated for multiple days of data, and the research shows that 58% of persistent contrails are avoided with a 0.48% increase in fuel consumption when averaged over a year.

Download or read book Control Estimation and Planning Algorithms for Aggressive Flight Using Onboard Sensing written by Adam Parker Bry and published by . This book was released on 2012 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis is motivated by the problem of fixed-wing flight through obstacles using only on-board sensing. To that end, we propose novel algorithms in trajectory generation for fixed-wing vehicles, state estimation in unstructured 3D environments, and planning under uncertainty. Aggressive flight through obstacles using on-board sensing involves nontrivial dynamics, spatially varying measurement properties, and obstacle constraints. To make the planning problem tractable, we restrict the motion plan to a nominal trajectory stabilized with an approximately linear estimator and controller. This restriction allows us to predict distributions over future states given a candidate nominal trajectory. Using these distributions to ensure a bounded probability of collision, the algorithm incrementally constructs a graph of trajectories through state space, while efficiently searching over candidate paths through the graph at each iteration. This process results in a search tree in belief space that provably converges to the optimal path. We analyze the algorithm theoretically and also provide simulation results demonstrating its utility for balancing information gathering to reduce uncertainty and finding low cost paths. Our state estimation method is driven by an inertial measurement unit (IMU) and a planar laser range finder and is suitable for use in real-time on a fixed-wing micro air vehicle (MAV). The algorithm is capable of maintaining accurate state estimates during aggressive flight in unstructured 3D environments without the use of an external positioning system. The localization algorithm is based on an extension of the Gaussian Particle Filter. We partition the state according to measurement independence relationships and then calculate a pseudo-linear update which allows us to use 25x fewer particles than a naive implementation to achieve similar accuracy in the state estimate. Using a multi-step forward fitting method we are able to identify the noise parameters of the IMU leading to high quality predictions of the uncertainty associated with the process model. Our process and measurement models integrate naturally with an exponential coordinates representation of the attitude uncertainty. We demonstrate our algorithms experimentally on a fixed-wing vehicle flying in a challenging indoor environment. The algorithm for generating the trajectories used in the planning process computes a transverse polynomial offset from a nominal Dubins path. The polynomial offset allows us to explicitly specify transverse derivatives in terms of linear equality constraints on the coefficients of the polynomial, and minimize transverse derivatives by using a Quadratic Program (QP) on the polynomial coefficients. This results in a computationally cheap method for generating paths with continuous heading, roll angle, and roll rate for the fixed-wing vehicle, which is fast enough to run in the inner loop of the RRBT.

Download or read book Advancing Aerial Mobility written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2020-07-15 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced aerial mobility is a newly emerging industry that aims to develop and operate new air vehicles potentially capable of safe, reliable, and low-noise vertical flight. The world has seen a recent increase in the adoption of electric vertical lift aircraft for urban, suburban and rural operations. These new innovations and technologies change the way that we move cargo and people, affecting industries across the economy. These changes will challenge today's airspace monitoring systems and regulatory environment. The U.S. government and its regulatory agencies need technical guidance to facilitate the development of these technologies, and to create the regulatory framework to foster the growth of this vertical flight industry to the benefit of the aviation industry. Advancing Aerial Mobility evaluates the potential benefits and challenges associated with this emerging industry. This report provides recommendations that seek to foster an environment in which the nation can maintain its leading position in developing, deploying, and embracing these new technologies. This publication presents a national vision for advanced aerial mobility, market evolution, and safety and security management.

Download or read book On line Planning of Collision Free Trajectories in Dynamic and Uncertain Environments written by Ferit Yegenoglu and published by . This book was released on 1989 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Principles of Robot Motion written by Howie Choset and published by MIT Press. This book was released on 2005-05-20 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: A text that makes the mathematical underpinnings of robot motion accessible and relates low-level details of implementation to high-level algorithmic concepts. Robot motion planning has become a major focus of robotics. Research findings can be applied not only to robotics but to planning routes on circuit boards, directing digital actors in computer graphics, robot-assisted surgery and medicine, and in novel areas such as drug design and protein folding. This text reflects the great advances that have taken place in the last ten years, including sensor-based planning, probabalistic planning, localization and mapping, and motion planning for dynamic and nonholonomic systems. Its presentation makes the mathematical underpinnings of robot motion accessible to students of computer science and engineering, rleating low-level implementation details to high-level algorithmic concepts.

Download or read book PRIMA 2016 Principles and Practice of Multi Agent Systems written by Matteo Baldoni and published by Springer. This book was released on 2016-08-10 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2016, held in Phuket, Thailand, in August 22-26, 2016. The 16 revised full papers presented together with two invited papers, 9 short papers and three extended abstracts were carefully reviewed and selected from 50 submissions. The intention of the papers is to showcase research in several domains, ranging from foundations of agent theory and engineering aspects of agent systems, to emerging interdisciplinary areas of agent-based research.

Download or read book Numerical Models for Differential Problems written by Alfio Quarteroni and published by Springer Science & Business. This book was released on 2014-04-25 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this text, we introduce the basic concepts for the numerical modelling of partial differential equations. We consider the classical elliptic, parabolic and hyperbolic linear equations, but also the diffusion, transport, and Navier-Stokes equations, as well as equations representing conservation laws, saddle-point problems and optimal control problems. Furthermore, we provide numerous physical examples which underline such equations. We then analyze numerical solution methods based on finite elements, finite differences, finite volumes, spectral methods and domain decomposition methods, and reduced basis methods. In particular, we discuss the algorithmic and computer implementation aspects and provide a number of easy-to-use programs. The text does not require any previous advanced mathematical knowledge of partial differential equations: the absolutely essential concepts are reported in a preliminary chapter. It is therefore suitable for students of bachelor and master courses in scientific disciplines, and recommendable to those researchers in the academic and extra-academic domain who want to approach this interesting branch of applied mathematics.