Download or read book Perception for Control and Control for Perception of Vision based Autonomous Aerial Robots written by Eric Cristofalo and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The mission of this thesis is to develop visual perception and feedback control algorithms for autonomous aerial robots that are equipped with an onboard camera. We introduce light-weight algorithms that parse images from the robot's camera directly into feedback signals for control laws that improve perception quality. We emphasize the co-design, analysis, and implementation of the perception, planning, and control tasks to ensure that the entire autonomy pipeline is suitable for aerial robots with real-world constraints. The methods presented in this thesis further leverage perception for control and control for perception: the former uses perception to inform the robot how to act while the later uses robotic control to improve the robot's perception of the world. Perception in this work refers to the processing of raw sensor measurements and the estimation of state values while control refers to the planning of useful robot motions and control inputs based on these state estimates. The major capability that we enable is a robot's ability to sense this unmeasured scene geometry as well as the three-dimensional (3D) robot pose from images acquired by its onboard camera. Our algorithms specifically enable a UAV with an onboard camera to use control to reconstruct the 3D geometry of its environment in a both sparse sense and a dense sense, estimate its own global pose with respect to the environment, and estimate the relative poses of other UAVs and dynamic objects of interest in the scene. All methods are implemented on real robots with real-world sensory, power, communication, and computation constraints to demonstrate the need for tightly-coupled, fast perception and control in robot autonomy. Depth estimation at specific pixel locations is often considered to be a perception-specific task for a single robot. We instead control the robot to steer a sensor to improve this depth estimation. First, we develop an active perception controller that maneuvers a quadrotor with a downward facing camera according to the gradient of maximum uncertainty reduction for a sparse subset of image features. This allows us to actively build a 3D point cloud representation of the scene quickly and thus enabling fast situational awareness for the aerial robot. Our method reduces uncertainty more quickly than state-of-the-art approaches for approximately an order of magnitude less computation time. Second, we autonomously control the focus mechanism on a camera lens to build metric-scale, dense depth maps that are suitable for robotic localization and navigation. Compared to the depth data from an off-the-shelf RGB-D sensor (Microsoft Kinect), our Depth-from-Focus method recovers the depth for 88% of the pixels with no RGB-D measurements in near-field regime (0.0 - 0.5 meters), making it a suitable complimentary sensor for RGB-D. We demonstrate dense sensing on a ground robot localization application and with AirSim, an advanced aerial robot simulator. We then consider applications where groups of aerial robots with monocular cameras seek to estimate their pose, or position and orientation, in the environment. Examples include formation control, target tracking, drone racing, and pose graph optimization. Here, we employ ideas from control theory to perform the pose estimation. We first propose the tight-coupling of pairwise relative pose estimation with cooperative control methods for distributed formation control using quadrotors with downward facing cameras, target tracking in a heterogenous robot system, and relative pose estimation for competitive drone racing. We experimentally validate all methods with real-time perception and control implementations. Finally, we develop a distributed pose graph optimization method for networks of robots with noisy relative pose measurements. Unlike existing pose graph optimization methods, our method is inspired by control theoretic approaches to distributed formation control. We leverage tools from Lyapunov theory and multi-agent consensus to derive a relative pose estimation algorithm with provable performance guarantees. Our method also reaches consensus 13x faster than a state-of-the-art centralized strategy and reaches solutions that are approximately 6x more accurate than decentralized pose estimation methods. While the computation times between our method and the benchmarch distributed method are similar for small networks, ours outperforms the benchmark by a factor of 100 on networks with large numbers of robots (> 1000). Our approach is easy to implement and fast, making it suitable for a distributed backend in a SLAM application. Our methods will ultimately allow micro aerial vehicles to perform more complicated tasks. Our focus on tightly-coupled perception and control leads to algorithms that are streamlined for real aerial robots with real constraints. These robots will be more flexible for applications including infrastructure inspection, automated farming, and cinematography. Our methods will also enable more robot-to-robot collaboration since we present effective ways to estimate the relative pose between them. Multi-robot systems will be an important part of the robotic future as they are robust to the failure of individual robots and allow complex computation to be distributed amongst the agents. Most of all, our methods allow robots to be more self sufficient by utilizing their onboard camera and by accurately estimating the world's structure. We believe these methods will enable aerial robots to better understand our 3D world.

Download or read book Deep Learning for Robot Perception and Cognition written by Alexandros Iosifidis and published by Academic Press. This book was released on 2022-02-04 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. Presents deep learning principles and methodologies Explains the principles of applying end-to-end learning in robotics applications Presents how to design and train deep learning models Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more Uses robotic simulation environments for training deep learning models Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis

Download or read book Multi View Geometry Based Visual Perception and Control of Robotic Systems written by Jian Chen and published by CRC Press. This book was released on 2018-06-14 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes visual perception and control methods for robotic systems that need to interact with the environment. Multiple view geometry is utilized to extract low-dimensional geometric information from abundant and high-dimensional image information, making it convenient to develop general solutions for robot perception and control tasks. In this book, multiple view geometry is used for geometric modeling and scaled pose estimation. Then Lyapunov methods are applied to design stabilizing control laws in the presence of model uncertainties and multiple constraints.

Download or read book Aerial Robotic Workers written by George Nikolakopoulos and published by Butterworth-Heinemann. This book was released on 2022-11-05 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aerial Robotic Workers: Design, Modeling, Control, Vision and Their Applications provides an in-depth look at both theory and practical applications surrounding the Aerial Robotic Worker (ARW). Emerging ARWs are fully autonomous flying robots that can assist human operations through their agile performance of aerial inspections and interaction with the surrounding infrastructure. This book addresses all the fundamental components of ARWs, starting with the hardware and software components and then addressing aspects of modeling, control, perception of the environment, and the concept of aerial manipulators, cooperative ARWs, and direct applications. The book includes sample codes and ROS-based tutorials, enabling the direct application of the chapters and real-life examples with platforms already existing in the market. Addresses the fundamental problems of UAVs with the ability of utilizing aerial tools in the fields of modeling, control, navigation, cooperation, vision and interaction with the environment Includes open source codes and libraries, providing a complete set of information for readers to start their experimentation with UAVs, and more specifically, ARWs Provides multiple, real-life examples and codes in MATLAB and ROS

Download or read book Environmental Perception Technology for Unmanned Systems written by Xin Bi and published by Springer Nature. This book was released on 2020-09-30 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the principles and technology of environmental perception in unmanned systems. With the rapid development of a new generation of information technologies such as automatic control and information perception, a new generation of robots and unmanned systems will also take on new importance. This book first reviews the development of autonomous systems and subsequently introduces readers to the technical characteristics and main technologies of the sensor. Lastly, it addresses aspects including autonomous path planning, intelligent perception and autonomous control technology under uncertain conditions. For the first time, the book systematically introduces the core technology of autonomous system information perception.

Download or read book Dynamic Vision for Perception and Control of Motion written by Ernst Dieter Dickmanns and published by Springer Science & Business Media. This book was released on 2007-06-02 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book on autonomous road-following vehicles brings together twenty years of innovation in the field. The book uniquely details an approach to real-time machine vision for the understanding of dynamic scenes, viewed from a moving platform that begins with spatio-temporal representations of motion for hypothesized objects whose parameters are adjusted by well-known prediction error feedback and recursive estimation techniques.

Download or read book Methods for Online Predictive Control of Multi rotor Aerial Robots with Perception driven Tasks Subject to Sensing and Actuation Constraints written by Martin Jacquet and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drones have an increasing place in numerous applications already started to take advantage from those, in particular in the fields of photography and video making, or simply for leisure activities. Simultaneously, the picture of autonomous aerial robots widely spread as a mark of innovation, such that many civilian of industrial applications are now envisioned through this aspect. One could cite, for instance, the persistent idea of aerial home delivery of goods, exploited by many companies. Another spread use-case is the deployment of fleets of aerial robots for monitoring activities, in hard-to-access environments, such as high mountains.The aerial robotics research community is active from numerous years, and the state of the art keeps improving, being through the conception of novel, more adaptive control algorithms, or the improvements of the hardware designs, opening new ranges of possibilities.The deployment of such robots in the scope of applications in uncontrolled environments comes with a lot of challenges, in particular regarding the perception of the surroundings. Exteroceptive sensors are indeed mandatory for most of autonomous applications. Among those sensors, cameras hold a peculiar position.It is on the one hand due to the simple onboard integration with their small size and weight,and on the other hand to the design of human-made environments, which are heavily built around visual markers (signs, illuminated signals...) However, maintaining visibility over objects or phenomenon often collide with the motion requirements of the robot, or with the tasks to which it is assigned. This effect is prominent when using underactuated robots, which are the most widely spread types of aerial vehicles, partly because of their higher energy efficiency. This property implies a strong coupling between position and orientation: the robot needs to tilt to move, and corollary moves when it tilts, thus altering the sensor bearing.From this assessment, the robotics community works to produce sensorimotor algorithms, able to produce motions while accounting for perception.This thesis takes place in this context, aiming at proposing such control methods to enforce the visibility over a phenomenon of interest through the onboard sensors. Moreover, to ensure the feasibility of the generated commands, it is required to account for the various actuation limitations of the robots. Finally, this thesis devotes to propose generic formulations, thus avoiding to propose ad hoc solutions, which would be contingent to a specific problem.To tackles these aspects under a common formalism, the proposed solutions are based on optimal and predictive control policies. These are based on numerical optimization, implying the need of accurate models, and thus accounting for the system nonlinearities, which are often disregarded for simplification.The contributions of this these are the aggregation of the various concepts in a common paradigm,and the formalization of the various mathematical functions transcribing the objectives and constraints related to perception. This paradigm is used in the scope of several applications related to usual perception-driven tasks in aerial robotics, namely the tracking of dynamic phenomenon, the improvement of this tracking, or the visual-inertial localization. Finally, the proposed solutions are implemented and tested in simulations and on real aerial robots.The work conducted throughout this thesis led to various publications in international peer-reviewed conferences and journals. All the related software production from these works are published open-source for the robotics community.

Download or read book Robust Perception from Optical Sensors for Reactive Behaviors in Autonomous Robotic Vehicles written by Alexander Schaub and published by Springer Vieweg. This book was released on 2017-07-27 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Alexander Schaub examines how a reactive instinctive behavior, similar to instinctive reactions as incorporated by living beings, can be achieved for intelligent mobile robots to extend the classic reasoning approaches. He identifies possible applications for reactive approaches, as they enable a fast response time, increase robustness and have a high abstraction ability, even though reactive methods are not universally applicable. The chosen applications are obstacle avoidance and relative positioning – which can also be utilized for navigation – and a combination of both. The implementation of reactive instinctive behaviors for the identified tasks is then validated in simulation together with real world experiments.

Download or read book Visual Perception and Robotic Manipulation written by Geoffrey Taylor and published by Springer. This book was released on 2008-08-18 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book moves toward the realization of domestic robots by presenting an integrated view of computer vision and robotics, covering fundamental topics including optimal sensor design, visual servo-ing, 3D object modelling and recognition, and multi-cue tracking, emphasizing robustness throughout. Covering theory and implementation, experimental results and comprehensive multimedia support including video clips, VRML data, C++ code and lecture slides, this book is a practical reference for roboticists and a valuable teaching resource.

Download or read book Multi view Geometry Based Visual Perception and Control of Robotic Systems written by Jian Chen and published by CRC Press. This book was released on 2018 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes visual perception and control methods for robotic systems that need to interact with the environment. Multiple view geometry is utilized to extract low-dimensional geometric information from abundant and high-dimensional image information, making it convenient to develop general solutions for robot perception and control tasks. In this book, multiple view geometry is used for geometric modeling and scaled pose estimation. Then Lyapunov methods are applied to design stabilizing control laws in the presence of model uncertainties and multiple constraints.

Download or read book Active Perception and Robot Vision written by Arun K. Sood and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 747 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent robotics has become the focus of extensive research activity. This effort has been motivated by the wide variety of applications that can benefit from the developments. These applications often involve mobile robots, multiple robots working and interacting in the same work area, and operations in hazardous environments like nuclear power plants. Applications in the consumer and service sectors are also attracting interest. These applications have highlighted the importance of performance, safety, reliability, and fault tolerance. This volume is a selection of papers from a NATO Advanced Study Institute held in July 1989 with a focus on active perception and robot vision. The papers deal with such issues as motion understanding, 3-D data analysis, error minimization, object and environment modeling, object detection and recognition, parallel and real-time vision, and data fusion. The paradigm underlying the papers is that robotic systems require repeated and hierarchical application of the perception-planning-action cycle. The primary focus of the papers is the perception part of the cycle. Issues related to complete implementations are also discussed.

Download or read book Active Robot Vision written by H. I. Christensen and published by World Scientific. This book was released on 1993 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the series in Machine Perception and Artificial Intelligence, this book covers subjects including the Harvard binocular head; heads, eyes, and head-eye systems; a binocular robot head with torsional eye movements; and escape and dodging behaviours for reactive control.

Download or read book Vision based Perception For Autonomous Robotic Manipulation written by Dinh-Cuong Hoang and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Control of Multiple Robots Using Vision Sensors written by Miguel Aranda and published by Springer. This book was released on 2017-05-11 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph introduces novel methods for the control and navigation of mobile robots using multiple-1-d-view models obtained from omni-directional cameras. This approach overcomes field-of-view and robustness limitations, simultaneously enhancing accuracy and simplifying application on real platforms. The authors also address coordinated motion tasks for multiple robots, exploring different system architectures, particularly the use of multiple aerial cameras in driving robot formations on the ground. Again, this has benefits of simplicity, scalability and flexibility. Coverage includes details of: a method for visual robot homing based on a memory of omni-directional images; a novel vision-based pose stabilization methodology for non-holonomic ground robots based on sinusoidal-varying control inputs; an algorithm to recover a generic motion between two 1-d views and which does not require a third view; a novel multi-robot setup where multiple camera-carrying unmanned aerial vehicles are used to observe and control a formation of ground mobile robots; and three coordinate-free methods for decentralized mobile robot formation stabilization. The performance of the different methods is evaluated both in simulation and experimentally with real robotic platforms and vision sensors. Control of Multiple Robots Using Vision Sensors will serve both academic researchers studying visual control of single and multiple robots and robotics engineers seeking to design control systems based on visual sensors.

Download or read book Introduction to Autonomous Mobile Robots second edition written by Roland Siegwart and published by MIT Press. This book was released on 2011-02-18 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a comprehensive introduction to all aspects of mobile robotics, from algorithms to mechanisms. Mobile robots range from the Mars Pathfinder mission's teleoperated Sojourner to the cleaning robots in the Paris Metro. This text offers students and other interested readers an introduction to the fundamentals of mobile robotics, spanning the mechanical, motor, sensory, perceptual, and cognitive layers the field comprises. The text focuses on mobility itself, offering an overview of the mechanisms that allow a mobile robot to move through a real world environment to perform its tasks, including locomotion, sensing, localization, and motion planning. It synthesizes material from such fields as kinematics, control theory, signal analysis, computer vision, information theory, artificial intelligence, and probability theory. The book presents the techniques and technology that enable mobility in a series of interacting modules. Each chapter treats a different aspect of mobility, as the book moves from low-level to high-level details. It covers all aspects of mobile robotics, including software and hardware design considerations, related technologies, and algorithmic techniques. This second edition has been revised and updated throughout, with 130 pages of new material on such topics as locomotion, perception, localization, and planning and navigation. Problem sets have been added at the end of each chapter. Bringing together all aspects of mobile robotics into one volume, Introduction to Autonomous Mobile Robots can serve as a textbook or a working tool for beginning practitioners. Curriculum developed by Dr. Robert King, Colorado School of Mines, and Dr. James Conrad, University of North Carolina-Charlotte, to accompany the National Instruments LabVIEW Robotics Starter Kit, are available. Included are 13 (6 by Dr. King and 7 by Dr. Conrad) laboratory exercises for using the LabVIEW Robotics Starter Kit to teach mobile robotics concepts.

Download or read book Artificial Vision for Mobile Robots written by Nicholas Ayache and published by MIT Press. This book was released on 1991 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: To give mobile robots real autonomy, and to permit them to act efficiently in a diverse, cluttered, and changing environment, they must be equipped with powerful tools for perception and reasoning. Artificial Vision for Mobile Robots presents new theoretical and practical tools useful for providing mobile robots with artificial vision in three dimensions, including passive binocular and trinocular stereo vision, local and global 3D map reconstructions, fusion of local 3D maps into a global 3D map, 3D navigation, control of uncertainty, and strategies of perception. Numerous examples from research carried out at INRIA with the Esprit Depth and Motion Analysis project are presented in a clear and concise manner. Nicolas Ayache is Research Director at INRIA, Le Chesnay, France. Contents. General Introduction. Stereo Vision. Introduction. Calibration. Image Representation. Binocular Stereo Vision Constraints. Binocular Stereo Vision Algorithms. Experiments in Binocular Stereo Vision. Trinocular Stereo Vision, Outlook. Multisensory Perception. Introduction. A Unified Formalism. Geometric Representation. Construction of Visual Maps. Combining Visual Maps. Results: Matching and Motion. Results: Matching and Fusion. Outlook.

Download or read book Handling Uncertainty and Networked Structure in Robot Control written by Lucian Bușoniu and published by Springer. This book was released on 2016-02-06 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on two challenges posed in robot control by the increasing adoption of robots in the everyday human environment: uncertainty and networked communication. Part I of the book describes learning control to address environmental uncertainty. Part II discusses state estimation, active sensing, and complex scenario perception to tackle sensing uncertainty. Part III completes the book with control of networked robots and multi-robot teams. Each chapter features in-depth technical coverage and case studies highlighting the applicability of the techniques, with real robots or in simulation. Platforms include mobile ground, aerial, and underwater robots, as well as humanoid robots and robot arms. Source code and experimental data are available at http://extras.springer.com. The text gathers contributions from academic and industry experts, and offers a valuable resource for researchers or graduate students in robot control and perception. It also benefits researchers in related areas, such as computer vision, nonlinear and learning control, and multi-agent systems.