Download or read book Path Planning for Motion Dependent State Estimation on Micro Aerial Vehicles written by Markus W. Achtelik (Ingénieur mécanicien.) and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mechatronics and Robotics written by Marina Indri and published by CRC Press. This book was released on 2020-11-24 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The term “mechatronics” was coined in 1969, merging “mecha” from mechanism and “tronics” from electronics, to reflect the original idea at the basis of this discipline, that is, the integration of electrical and mechanical systems into a single device. The spread of this term, and of mechatronics itself, has been growing in the years, including new aspects and disciplines, like control engineering, computer engineering and communication/information engineering. Nowadays mechatronics has a well-defined and fundamental role, in strict relation with robotics. Drawing a sharp border between mechatronics and robotics is impossible, as they share many technologies and objectives. Advanced robots could be defined as mechatronic devices equipped with a “smart brain”, but there are also up-to-date mechatronic devices, used in tight interaction with humans, that are governed by smart architectures (for example, for safety purposes). Aim of this book is to offer a wide overview of new research trends and challenges for both mechatronics and robotics, through the contribution of researchers from different institutions, providing their view on specific subjects they consider as “hot topics” in both fields, with attention to new fields of application, new challenges to the research communities and new technologies available. The reader of this book will enjoy the various contributions, as they have been prepared with actual applications in mind, along a journey from advanced actuators and sensors to human-robot interaction, through robot control, navigation, planning and programming issues. The book presents several state-of-the-art solutions, like multiple-stage actuation to cope with conflicting specification of large motion-spans, ultra-high accuracy, model-based control for high-tech mechatronic systems, modern approaches of software systems engineering to robotics, aand humanoids for human assistance. The reader can also find new techniques in approaching the design of mechatronic systems in some possible industrial and service robotics scenarios, with a particular attention for the interaction between humans and mechanisms.

Download or read book Motion Planning for Micro Aerial Vehicles written by Sikang Liu and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Micro Aerial Vehicle (MAV) is capable of agile motion in 3D making it an ideal platform for developments of planning and control algorithms. For fully autonomous MAV systems, it is essential to plan motions that are both dynamically feasible and collision-free in cluttered environments. Recent work demonstrates precise control of MAVs using time-parameterized trajectories that satisfy feasibility and safety requirements. However, planning such trajectories is non-trivial, especially when considering constraints, such as optimality and completeness. For navigating in unknown environments, the capability for fast re-planning is also critical. Considering all of these requirements, motion planning for MAVs is a challenging problem. In this thesis, we examine trajectory planning algorithms for MAVs and present methodologies that solve a wide range of planning problems. We first introduce path planning and geometric control methods, which produce spatial paths that are inadequate for high speed flight, but can be used to guide trajectory optimization. We then describe optimization-based trajectory planning and demonstrate this method for solving navigation problems in complex 3D environments. When the initial state is not fixed, an optimization-based method is prone to generate sub-optimal trajectories. To address this challenge, we propose a search-based approach using motion primitives to plan resolution complete and sub-optimal trajectories. This algorithm can also be used to solve planning problems with constraints such as motion uncertainty, limited field-of-view and moving obstacles. The proposed methods can run in real time and are applicable for real-world autonomous navigation, even with limited on-board computational resources. This thesis includes a carefully analysis of the strengths and weaknesses of our planning paradigm and algorithms, and demonstration of their performance through simulation and experiments.

Download or read book Path Planning for Vehicles Operating in Uncertain 2D Environments written by Viacheslav Pshikhopov and published by Butterworth-Heinemann. This book was released on 2017-01-28 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Path Planning for Vehicles Operating in Uncertain 2D-environments presents a survey that includes several path planning methods developed using fuzzy logic, grapho-analytical search, neural networks, and neural-like structures, procedures of genetic search, and unstable motion modes. Presents a survey of accounting limitations imposed by vehicle dynamics Proposes modified and new original methods, including neural networking, grapho-analytical, and nature-inspired Gives tools for a novice researcher to select a method that would suit their needs or help to synthesize new hybrid methods

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 Adaptive Path Planning for Navigation and Sensing of Micro Aerial Vehicles written by Seyed Abbas Sadat Kooch Mohtasham and published by . This book was released on 2016 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: Micro Aerial Vehicles (MAVs) have gained much attention as data collection and sensing platforms. Professionals in many fields can access rich sensory data with fast update rates by performing automated aerial surveys using MAVs. However, these robots have limited payloads and short flight times. Therefore, it is useful to perform a task with light and low-powered sensors and as quickly as possible. In this proposal, we consider some of the fundamental tasks performed by MAVs and propose methods by which a MAV can achieve these tasks more efficiently and robustly. In the first part of this thesis, we consider the task of navigation in which a MAV, using visual Simultaneous Localization and Mapping (SLAM) to map the environment and localize itself within it, moves from its current location to a goal location. As SLAM is highly dependent on the visibility of visual features, we propose an adaptive path planning approach that avoids visually-poor regions of the environment and can generate safe trajectories for the MAV to perform the navigation task. In the second part, an aerial coverage task is considered where the MAV must map interesting regions with initially unknown locations. Rather than using an exhaustive 'lawnmower' coverage pattern that sweeps the entire region uniformly, we propose non-uniform coverage strategies that adaptively cover all the interesting regions with high resolution and coarsely sweep the rest of the area. The proposed methods generate shorter trajectories compared to a uniform lawnmower pattern. In the last part of the thesis, we assume a time/energy budget for the vehicle and consider specific costs for different manoeuvres of the MAV. We introduce a novel problem of guaranteeing complete coverage of an area at low resolution, while identifying regions of interest (ROIs), and locally surveying as much of the ROIs at high resolution as the battery allows. Three different policies are proposed to decide when to switch between the coarse survey and high resolution imagery data collection.

Download or read book Modeling Control State Estimation and Path Planning Methods for Autonomous Multirotor Aerial Robots written by Christos Papachristos and published by . This book was released on 2018 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: This review paper aims to provide an overview of core modeling, control, estimation, and planning concepts and approaches for micro aerial robots of the rotorcraft class. A comprehensive description of a set of methods that enable automated flight control, state estimation in GPS–denied environments, as well as path planning techniques for autonomous exploration is provided, and serves as a holistic point of reference for those interested in the field of unmanned aerial systems. Further discussion for other applications of aerial robots concludes this manuscript.

Download or read book Aerial Manipulation written by Matko Orsag and published by Springer. This book was released on 2017-09-19 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is a thorough treatment of the rapidly growing area of aerial manipulation. It details all the design steps required for the modeling and control of unmanned aerial vehicles (UAV) equipped with robotic manipulators. Starting with the physical basics of rigid-body kinematics, the book gives an in-depth presentation of local and global coordinates, together with the representation of orientation and motion in fixed- and moving-coordinate systems. Coverage of the kinematics and dynamics of unmanned aerial vehicles is developed in a succession of popular UAV configurations for multirotor systems. Such an arrangement, supported by frequent examples and end-of-chapter exercises, leads the reader from simple to more complex UAV configurations. Propulsion-system aerodynamics, essential in UAV design, is analyzed through blade-element and momentum theories, analysis which is followed by a description of drag and ground-aerodynamic effects. The central part of the book is dedicated to aerial-manipulator kinematics, dynamics, and control. Based on foundations laid in the opening chapters, this portion of the book is a structured presentation of Newton–Euler dynamic modeling that results in forward and backward equations in both fixed- and moving-coordinate systems. The Lagrange–Euler approach is applied to expand the model further, providing formalisms to model the variable moment of inertia later used to analyze the dynamics of aerial manipulators in contact with the environment. Using knowledge from sensor data, insights are presented into the ways in which linear, robust, and adaptive control techniques can be applied in aerial manipulation so as to tackle the real-world problems faced by scholars and engineers in the design and implementation of aerial robotics systems. The book is completed by path and trajectory planning with vision-based examples for tracking and manipulation.

Download or read book Improved State Estimation for Miniature Air Vehicles written by Andrew Mark Eldredge and published by . This book was released on 2006 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research in Unmanned Air Vehicles (UAV's) continues to push the limitations of size and weight. As technical advances have made UAV's smaller and less expensive, they have become more flexible and extensive in their roles. To continue using smaller and less expensive components while retaining and even enhancing performance requires more sophisticated processing of sensor data in order for the UAV to accurately determine its state and thereby allow the use of feedback in controlling the aircraft automatically. This work presents a three-stage state-estimation scheme for the class of UAV's know as Miniature Air Vehicles (MAV's). The first stage estimates pitch and roll, the second stage estimates heading, and the third stage produces a position estimate and an estimate of wind speed and direction. All three stages make use of the extended Kalman filter, a framework for using a system dynamic model to predict future states and to update the predictions using weighted sensor measurements as they become available, where the weighting is based on the relative uncertainty of the dynamic model and the sensors. Using the three-stage state esti-mation scheme, significant improvements in the estimation of pitch, roll and heading have been achieved in simulation and flight testing. Performance of the navigation (position and wind) stage is comparable to an existing baseline algorithms for position and wind, and shows additional promise for use in dead reckoning when GPS updates become unavailable.

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 Journal of Guidance Control and Dynamics written by and published by . This book was released on 2009 with total page 954 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 Path Planning with Dynamic Obstacles and Resource Constraints written by Alán Casea Cortez and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis considers path planning with resource constraints and dynamic obstacles for an unmanned aerial vehicle (UAV), modeled as a Dubins agent. Incorporating dynamic obstacles and resource constraints into the path planning problem designs a model that is more realistic of what an agent will encounter during its missions. A resource constraint is a path dependent load variable, such as noise or probability of detection by radar, that accrues as the agent moves towards the goal position. The resource constraint represents the total cumulative noise disturbance created by the UAV along its trajectory during flight in or around an urban area. By prescribing a maximum allowable cumulative noise disturbance, the UAV can be constrained to follow appropriate noise regulations while navigating in an urban environment. Hazards such as storms, turbulence, and ice are important to consider during the path planning stage as dynamic obstacles because these hazards can damage or destroy the UAV if encountered. These weather hazard dynamics can be recorded and learned and occur in a time-scale that is within the duration of the flight of the UAV. Incorporating these obstacles into the path planner can allow the agent to forecast how the weather will change and have it react accordingly. Obstacles such as other aerial vehicles that are handled by detect-and-avoid methods will not be looked at in this thesis. Dynamic obstacles can pose a challenge as the computation time and storage needed increases the longer it takes to find the path. Ice data from the Aviation Weather Service was employed to create training data sets for learning dynamic weather (ice) phenomena. Dynamic Mode Decomposition (DMD) was used to learn and propagate the evolution of ice conditions at flight level. These obstacles were integrated into a Hybrid $A^\star$ path-planner with backtracking to handle resource constraints. It is shown through numerical simulations that the agent is able to navigate around the dynamic obstacles to find the minimum time path to its goal. The use of Dynamic Mode Decomposition to predict and learn the dynamics of the ice hazards was a success in that it was able to recreate and construct the obstacles at future time steps.

Download or read book Path Planning for Fixed Wing Unmanned Aerial Vehicles written by Daniel Schneider and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 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.

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.