Overview Of Rgbd Slam Approaches

Author: Tobias Hollarek
Editor: GRIN Verlag
ISBN: 3656546266
File Size: 54,31 MB
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Seminar paper from the year 2012 in the subject Computer Science - Applied, grade: 1,3, Technical University of Munich (Lehrstuhl für Echtzeitsysteme und Robotik), course: Hauptseminar Computer Vision & Visual Tracking for Robotic Applications SS2012, language: English, abstract: In this paper I will introduce the reader to RGB-D SLAM which has become the focus of interest for many researchers lately. This is due to the development and distribution of cheap RGB-D sensor devices such as the Microsoft Kinect. After an introduction I will present which steps have to be taken to implement a working SLAM system using RGB-D data. In section three I will introduce three different approaches and will present how they implemented the SLAM and what they did to increase speed, accuracy and robustness of their algorithms. I will then compare the results of all approaches. In the next section I will present what optimization methods two of these approaches implemented to improve their mapping by optimizing with a global approach. These implementations also are reviewed and compared as far as that was possible. In section five I will present how two different approaches store the mapping after all calculation is done in a sophisticated and compact way. Finally I will conclude over the results I collected and give an outlook on possible future developments.

Slam And Localization Of People With A Mobile Robot Using A Rgb D Sensor

Author: Francisco Ferrer Sales
Editor: University of Coimbra
ISBN:
File Size: 48,50 MB
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The evolution of Robotics lead us to aspire replacing human beings by autonomous robotic systems in the most discomforting or dangerous situations, and even to have them performing tasks that humans are incapable of. Such situations are often encountered when facing a catastrophic scenario and human rescue teams put themselves at risk in their heroic attempt to rescue victims. In nowadays society, the human life is highly valued and, consequently, Search and Rescue (SaR) missions became of extreme importance, precisely because their accomplishment can save several human lives. For that reason, rescue teams are heavily trained and, since they also comprise human beings, heavily equipped. However, they often lack technological tools to perform their mission better and in safety. The main objective of this work is to study, develop and validate a fully-integrated robotic system to eventually explore catastrophic scenarios, by providing a map of the area and the people it detected while performing its task. This is a vital information in SaR missions, and this work aims at achieving this without risking a human life in the process. To that end, a mobile robot with a Red-Blue-Green and Depth (RGB-D) sensor mounted on its top was used. Furthermore, all approaches and methods were implemented in Robot Operating System (ROS) and thoroughly analyzed to assess their accuracy and performance. However, due to hardware limitations, the results are comprehensively not optimal, but they still provide useful information that might be of great help in SaR missions. Moreover, the study and analysis of this type of sensor and its usability are valuable and are now available for upcoming developments. This work is part of the Cooperation between Human and rObotic teams in catastroPhic INcidents (CHOPIN) project, which intends to develop a support system for small-scale SaR missions in urban catastrophic scenarios by exploiting human-robot cooperation.

Image Analysis And Recognition

Author: Mohamed Kamel
Editor: Springer
ISBN: 3319208012
File Size: 16,62 MB
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This book constitutes the thoroughly refereed proceedings of the 12th International Conference on Image Analysis and Recognition, ICIAR 2015, held in Niagara Falls, ON, Canada, in July 2015. The 55 revised full papers and 5 short papers presented were carefully reviewed and selected from 80 submissions. The papers are organized in the following topical sections: image quality assessment; image enhancement; image segmentation, registration and analysis; image coding, compression and encryption; dimensionality reduction and classification; biometrics; face description, detection and recognition; human activity recognition; robotics and 3D vision; medical image analysis; and applications.

Computer Vision Eccv 2018

Author: Vittorio Ferrari
Editor: Springer
ISBN: 3030012255
File Size: 32,48 MB
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The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.

Rgb D Image Analysis And Processing

Author: Paul L. Rosin
Editor: Springer Nature
ISBN: 3030286037
File Size: 63,15 MB
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This book focuses on the fundamentals and recent advances in RGB-D imaging as well as covering a range of RGB-D applications. The topics covered include: data acquisition, data quality assessment, filling holes, 3D reconstruction, SLAM, multiple depth camera systems, segmentation, object detection, salience detection, pose estimation, geometric modelling, fall detection, autonomous driving, motor rehabilitation therapy, people counting and cognitive service robots. The availability of cheap RGB-D sensors has led to an explosion over the last five years in the capture and application of colour plus depth data. The addition of depth data to regular RGB images vastly increases the range of applications, and has resulted in a demand for robust and real-time processing of RGB-D data. There remain many technical challenges, and RGB-D image processing is an ongoing research area. This book covers the full state of the art, and consists of a series of chapters by internationally renowned experts in the field. Each chapter is written so as to provide a detailed overview of that topic. RGB-D Image Analysis and Processing will enable both students and professional developers alike to quickly get up to speed with contemporary techniques, and apply RGB-D imaging in their own projects.

Advanced Concepts For Intelligent Vision Systems

Author: Jacques Blanc-Talon
Editor: Springer
ISBN: 3319486802
File Size: 53,29 MB
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This book constitutes the refereed proceedings of the 17th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2016, held in Lecce, Italy, in October 2016. The 64 revised full papers presented in this volume were carefully selected from 137 submissions. They deal with classical low-level image processing techniques; image and video compression; 3D; security and forensics; and evaluation methodologies.

Challenges In Automation Robotics And Measurement Techniques

Author: Roman Szewczyk
Editor: Springer
ISBN: 3319293575
File Size: 62,49 MB
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This book presents the set of papers accepted for presentation at the International Conference Automation, held in Warsaw, 2-4 March of 2016. It presents the research results presented by top experts in the fields of industrial automation, control, robotics and measurement techniques. Each chapter presents a thorough analysis of a specific technical problem which is usually followed by numerical analysis, simulation, and description of results of implementation of the solution of a real world problem. The presented theoretical results, practical solutions and guidelines will be valuable for both researchers working in the area of engineering sciences and for practitioners solving industrial problems.

Robot 2015 Second Iberian Robotics Conference

Author: Luís Paulo Reis
Editor: Springer
ISBN: 3319271490
File Size: 51,85 MB
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This book contains a selection of papers accepted for presentation and discussion at ROBOT 2015: Second Iberian Robotics Conference, held in Lisbon, Portugal, November 19th-21th, 2015. ROBOT 2015 is part of a series of conferences that are a joint organization of SPR – “Sociedade Portuguesa de Robótica/ Portuguese Society for Robotics”, SEIDROB – Sociedad Española para la Investigación y Desarrollo de la Robótica/ Spanish Society for Research and Development in Robotics and CEA-GTRob – Grupo Temático de Robótica/ Robotics Thematic Group. The conference organization had also the collaboration of several universities and research institutes, including: University of Minho, University of Porto, University of Lisbon, Polytechnic Institute of Porto, University of Aveiro, University of Zaragoza, University of Malaga, LIACC, INESC-TEC and LARSyS. Robot 2015 was focussed on the Robotics scientific and technological activities in the Iberian Peninsula, although open to research and delegates from other countries. The conference featured 19 special sessions, plus a main/general robotics track. The special sessions were about: Agricultural Robotics and Field Automation; Autonomous Driving and Driver Assistance Systems; Communication Aware Robotics; Environmental Robotics; Social Robotics: Intelligent and Adaptable AAL Systems; Future Industrial Robotics Systems; Legged Locomotion Robots; Rehabilitation and Assistive Robotics; Robotic Applications in Art and Architecture; Surgical Robotics; Urban Robotics; Visual Perception for Autonomous Robots; Machine Learning in Robotics; Simulation and Competitions in Robotics; Educational Robotics; Visual Maps in Robotics; Control and Planning in Aerial Robotics, the XVI edition of the Workshop on Physical Agents and a Special Session on Technological Transfer and Innovation.

Immersive Dynamic Scenes For Virtual Reality From A Single Rgb D Camera

Author: Po Kong Lai
Editor:
ISBN:
File Size: 23,46 MB
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In this thesis we explore the concepts and components which can be used as individual building blocks for producing immersive virtual reality (VR) content from a single RGB-D sensor. We identify the properties of immersive VR videos and propose a system composed of a foreground/background separator, a dynamic scene re-constructor and a shape completer. We initially explore the foreground/background separator component in the context of video summarization. More specifically, we examined how to extract trajectories of moving objects from video sequences captured with a static camera. We then present a new approach for video summarization via minimization of the spatial-temporal projections of the extracted object trajectories. New evaluation criterion are also presented for video summarization. These concepts of foreground/background separation can then be applied towards VR scene creation by extracting relative objects of interest. We present an approach for the dynamic scene re-constructor component using a single moving RGB-D sensor. By tracking the foreground objects and removing them from the input RGB-D frames we can feed the background only data into existing RGB-D SLAM systems. The result is a static 3D background model where the foreground frames are then super-imposed to produce a coherent scene with dynamic moving foreground objects. We also present a specific method for extracting moving foreground objects from a moving RGB-D camera along with an evaluation dataset with benchmarks. Lastly, the shape completer component takes in a single view depth map of an object as input and "fills in" the occluded portions to produce a complete 3D shape. We present an approach that utilizes a new data minimal representation, the {\em additive depth map}, which allows traditional 2D convolutional neural networks to accomplish the task. The additive depth map represents the amount of depth required to transform the input into the "back depth map" which would exist if there was a sensor exactly opposite of the input. We train and benchmark our approach using existing synthetic datasets and also show that it can perform shape completion on real world data without fine-tuning. Our experiments show that our data minimal representation can achieve comparable results to existing state-of-the-art 3D networks while also being able to produce higher resolution outputs.

Intelligent Autonomous Systems 13

Author: Emanuele Menegatti
Editor: Springer
ISBN: 3319083384
File Size: 78,99 MB
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This book describes the latest research accomplishments, innovations, and visions in the field of robotics as presented at the 13th International Conference on Intelligent Autonomous Systems (IAS), held in Padua in July 2014, by leading researchers, engineers, and practitioners from across the world. The contents amply confirm that robots, machines, and systems are rapidly achieving intelligence and autonomy, mastering more and more capabilities such as mobility and manipulation, sensing and perception, reasoning, and decision making. A wide range of research results and applications are covered, and particular attention is paid to the emerging role of autonomous robots and intelligent systems in industrial production, which reflects their maturity and robustness. The contributions have been selected through a rigorous peer-review process and contain many exciting and visionary ideas that will further galvanize the research community, spurring novel research directions. The series of biennial IAS conferences commenced in 1986 and represents a premiere event in robotics.

Inventive Communication And Computational Technologies

Author: G. Ranganathan
Editor: Springer Nature
ISBN: 9811501467
File Size: 71,31 MB
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This book gathers selected papers presented at the Inventive Communication and Computational Technologies conference (ICICCT 2019), held on 29–30 April 2019 at Gnanamani College of Technology, Tamil Nadu, India. The respective contributions highlight recent research efforts and advances in a new paradigm called ISMAC (IoT in Social, Mobile, Analytics and Cloud contexts). Topics covered include the Internet of Things, Social Networks, Mobile Communications, Big Data Analytics, Bio-inspired Computing and Cloud Computing. The book is chiefly intended for academics and practitioners working to resolve practical issues in this area.

Image And Graphics

Author: Yao Zhao
Editor: Springer
ISBN: 3319716077
File Size: 43,10 MB
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This three-volume set LNCS 10666, 10667, and 10668 constitutes the refereed conference proceedings of the 9th International Conference on Image and Graphics, ICIG 2017, held in Shanghai, China, in September 2017. The 172 full papers were selected from 370 submissions and focus on advances of theory, techniques and algorithms as well as innovative technologies of image, video and graphics processing and fostering innovation, entrepreneurship, and networking.

Proceedings Of The 2018 International Symposium On Experimental Robotics

Author: Jing Xiao
Editor: Springer Nature
ISBN: 3030339505
File Size: 44,86 MB
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In addition to the contributions presented at the 2018 International Symposium on Experimental Robotics (ISER 2018), this book features summaries of the discussions that were held during the event in Buenos Aires, Argentina. These summaries, authored by leading researchers and session organizers, offer important insights on the issues that drove the symposium debates. Readers will find cutting-edge experimental research results from a range of robotics domains, such as medical robotics, unmanned aerial vehicles, mobile robot navigation, mapping and localization, field robotics, robot learning, robotic manipulation, human–robot interaction, and design and prototyping. In this unique collection of the latest experimental robotics work, the common thread is the experimental testing and validation of new ideas and methodologies. The International Symposium on Experimental Robotics is a series of bi-annual symposia sponsored by the International Foundation of Robotics Research, whose goal is to provide a dedicated forum for experimental robotics research. In recent years, robotics has broadened its scientific scope, deepened its methodologies and expanded its applications. However, the significance of experiments remains at the heart of the discipline. The ISER gatherings are an essential venue where scientists can meet and have in-depth discussions on robotics based on this central tenet.

Robotics

Author: Fernando Santos Osório
Editor: Springer
ISBN: 331947247X
File Size: 65,72 MB
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This book constitutes the refereed proceedings of the 12th Latin American Robotics Symposium and Third Brazilian Symposium on Robotics, LARS 2015 / SBR 2015, held in Uberlândia, Brazil, in October/November 2015. The 17 revised full papers presented were carefully reviewed and selected from 80 submissions. The selected papers present a complete and solid reference of the state-of-the-art of intelligent robotics and automation research, covering the following areas: autonomous mobile robots, tele-operated and telepresence robots, human-robot interaction, trajectory control for mobile robots, autonomous vehicles, service-oriented robotic systems, semantic mapping, environment mapping, visual odometry, applications of RGB-D sensors, humanoid and biped robots, Robocup soccer robots, robot control, path planning, multiple vehicles and teams of robots. /div

Computer Vision Eccv 2018 Workshops

Author: Laura Leal-Taixé
Editor: Springer
ISBN: 3030110095
File Size: 26,60 MB
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The six-volume set comprising the LNCS volumes 11129-11134 constitutes the refereed proceedings of the workshops that took place in conjunction with the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.43 workshops from 74 workshops proposals were selected for inclusion in the proceedings. The workshop topics present a good orchestration of new trends and traditional issues, built bridges into neighboring fields, and discuss fundamental technologies and novel applications.

Pattern Recognition And Computer Vision

Author: Zhouchen Lin
Editor: Springer Nature
ISBN: 3030317269
File Size: 57,14 MB
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The three-volume set LNCS 11857, 11858, and 11859 constitutes the refereed proceedings of the Second Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2019, held in Xi’an, China, in November 2019. The 165 revised full papers presented were carefully reviewed and selected from 412 submissions. The papers have been organized in the following topical sections: Part I: Object Detection, Tracking and Recognition, Part II: Image/Video Processing and Analysis, Part III: Data Analysis and Optimization.

Perception For Control And Control For Perception Of Vision Based Autonomous Aerial Robots

Author: Eric Cristofalo
Editor:
ISBN:
File Size: 49,17 MB
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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.

Computer Vision Eccv 2020

Author: Andrea Vedaldi
Editor: Springer Nature
ISBN: 3030586219
File Size: 57,20 MB
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Intelligent Autonomous Systems 14

Author: Weidong Chen
Editor: Springer
ISBN: 3319480367
File Size: 10,42 MB
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This book describes the latest research advances, innovations, and visions in the field of robotics as presented by leading researchers, engineers, and practitioners from around the world at the 14th International Conference on Intelligent Autonomous Systems (IAS-14), held in Shanghai, China in July 2016. The contributions amply demonstrate that robots, machines and systems are rapidly achieving intelligence and autonomy, attaining more and more capabilities such as mobility and manipulation, sensing and perception, reasoning, and decision-making. They cover a wide range of research results and applications, and particular attention is paid to the emerging role of autonomous robots and intelligent systems in industrial production, which reflects their maturity and robustness. The contributions were selected by means of a rigorous peer-review process and highlight many exciting and visionary ideas that will further galvanize the research community and spur novel research directions. The series of biennial IAS conferences, which began in 1986, represents a premiere event in the field of robotics.

Proceedings Of 2018 Chinese Intelligent Systems Conference

Author: Yingmin Jia
Editor: Springer
ISBN: 9811322880
File Size: 69,31 MB
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These proceedings present selected research papers from CISC’18, held in Wenzhou, China. The topics include Multi-Agent Systems, Networked Control Systems, Intelligent Robots, Complex System Theory and Swarm Behavior, Event-Triggered Control and Data-Driven Control, Robust and Adaptive Control, Big Data and Brain Science, Process Control, Nonlinear and Variable Structure Control, Intelligent Sensor and Detection Technology, Deep learning and Learning Control Guidance, Navigation and Control of Flight Vehicles, and so on. Engineers and researchers from academia, industry, and government can get an insight view of the solutions combining ideas from multiple disciplines in the field of intelligent systems.