Download or read book MRSLAM Multi Robot Simultaneous Localization and Mapping written by João Alexandre Simões Martins and published by University of Coimbra. This book was released on 2013-09-01 with total page 67 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays, a collection of two or more autonomous mobile agents working together are denoted as teams or simply societies of mobile robots. In Multi-Robot Systems (MRS) robots are allowed to coordinate with each other in order to achieve a speci c goal. In these systems, robots are far less capable as an entity, but the real power lies in the cooperation of the team. The simplicity of MRS has produced a wide set of applications such as in military tasks , searching for survivors in disaster hit areas, parallel and simultaneous transportations of vehicles and delivery of payloads. The success of single-robot Simultaneous Localization and Mapping (SLAM) in the past two decades has led to research on Multi-Robot Simultaneous Localization and Mapping (MRSLAM). A team of robots is able to map an unknown environment faster and more and reliably. However, MRSLAM raises several challenging problems, including map fusion, unknown robot poses and scalability issues. Rao-Blackwellized Particle Filters (RBPFs) have been demonstrated as an eective solution to the problem of single robot Simultaneous Localization and Mapping (SLAM), and a few extensions to teams of robots exist. However, these approaches are usually characterized by strict assumptions on both communication bandwidth and prior knowledge on relative poses between teammates. In this dissertation, we describe in detail a distributed MRSLAM approach using RBPF in the case of possibly constrained communication and unknown relative initial poses using Robot Operating System (ROS). We consider the environment as a two dimensional space with several obstacles, which are explored by a team of cooperative mobile robots, equipped with laser sensors. In order to e ciently tackle the problem, the cooperation between agents and the memory space available for observations storage must be taken into account. Experimental results using a team of up to two robots in a large indoor area show the robustness and performance of the approach.
Download or read book Simultaneous Localization and Mapping for Mobile Robots Introduction and Methods written by Fernández-Madrigal, Juan-Antonio and published by IGI Global. This book was released on 2012-09-30 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: As mobile robots become more common in general knowledge and practices, as opposed to simply in research labs, there is an increased need for the introduction and methods to Simultaneous Localization and Mapping (SLAM) and its techniques and concepts related to robotics. Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods investigates the complexities of the theory of probabilistic localization and mapping of mobile robots as well as providing the most current and concrete developments. This reference source aims to be useful for practitioners, graduate and postgraduate students, and active researchers alike.
Download or read book Robotic Mapping and Exploration written by Cyrill Stachniss and published by Springer. This book was released on 2009-05-06 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Robotic Mapping and Exploration" is an important contribution in the area of simultaneous localization and mapping (SLAM) for autonomous robots, which has been receiving a great deal of attention by the research community in the latest few years. The contents are focused on the autonomous mapping learning problem. Solutions include uncertainty-driven exploration, active loop closing, coordination of multiple robots, learning and incorporating background knowledge, and dealing with dynamic environments. Results are accompanied by a rich set of experiments, revealing a promising outlook toward the application to a wide range of mobile robots and field settings, such as search and rescue, transportation tasks, or automated vacuum cleaning.
Download or read book Multi robot Simultaneous Localization and Mapping with Generalized Objects written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multi Robot FastSLAM written by Dilhan Balage and published by . This book was released on 2010 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Robust and Lightweight Localization and Dense Mapping for Multi robot Systems written by Yun Chang (Researcher in robotics) and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we propose novel approaches to robust multi-robot Simultaneous Localization and Mapping (SLAM). We explore multi-robot SLAM in both the centralized and distributed setting, with point-cloud or mesh-based representations to create a lightweight but dense map of the environment from vision or lidar data. We present and discuss four different approaches to multi-robot SLAM. The first approach, named Large-scale Autonomous Mapping and Positioning (LAMP), is a centralized lidar-based approach that creates a dense point-cloud map of the environment and uses incremental Pairwise Consistency Maximization (PCM) to reject outliers in the loop closure measurements. The second approach, named meshLAMP, is an extension of LAMP that uses Graduated Non-Convexity to reject ouliers and creates a lightweight mesh map of the environment. To address the limitations in communication range and scalability of the centralized approaches, we also present two distributed approaches. The first distributed approach, named Distributed, Online, and Outlier Resilient SLAM (DOOR-SLAM), is a vision-based distributed approach to multi-robot SLAM that extends PCM to reject outliers without relying on centralized computation. The last approach, named Kimera-Multi, is a visionbased distributed approach that uses PCM for outlier rejection, and extends the lightweight mesh-based mapping module in meshLAMP to operate in a distributed fashion and generate a semantic mesh map of the environment. We demonstrate the four approaches in a variety of conditions, from indoor environments to photo-realistic simulators, to underground spaces in the context of the DARPA Subterranean Challenge, and show that they are able to perform reliably in the field. We conclude by commenting on the advantages and possible improvements for each approach.
Download or read book Cooperative Localization and Navigation written by Chao Gao and published by CRC Press. This book was released on 2019-08-21 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book captures the latest results and techniques for cooperative localization and navigation drawn from a broad array of disciplines. It provides the reader with a generic and comprehensive view of modeling, strategies, and state estimation methodologies in that fields. It discusses the most recent research and novel advances in that direction, exploring the design of algorithms and architectures, benefits, and challenging aspects, as well as a potential broad array of disciplines, including wireless communication, indoor localization, robotics, emergency rescue, motion analysis, etc.
Download or read book Multi Agent Visual Slam Algorithms on Autonomous Robots written by Nezih Ergin Özkucur and published by LAP Lambert Academic Publishing. This book was released on 2010 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Simultaneous Localization and Mapping (SLAM) problem is one of the most challenging problems in robot navigation. The problem addresses autonomously exploring and mapping an unknown environment without prior knowledge (of features). The robot should generate the map of the environment and estimate its pose with respect to the map. An extension of this problem to the distributed multi-robot platform is a popular research topic for its challenges and commitments. Multiple cooperative robots exploring an area would decrease exploration time and increase the accuracy. This work introduces the application of two successful SLAM solution techniques to the multi-robot domain using visual sensors and non-unique landmarks. There are two contributions to the literature: Evolutionary Strategies (ES) is used to calibrate the parameters of the Extended Kalman Filter-SLAM (EKF-SLAM) method with supervised data, and a novel map merging method with uncertainty propagation is introduced for the Fast-SLAM algorithm. The developed algorithms are tested in both simulated and real robot experiments and the improvements and applicability of the developed methods are shown with the results.
Download or read book Parallel and Distributed Map Merging and Localization written by Rosario Aragues and published by Springer. This book was released on 2015-10-31 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work examines the challenges of distributed map merging and localization in multi-robot systems, which enables robots to acquire the knowledge of their surroundings needed to carry out coordinated tasks. After identifying the main issues associated with this problem, each chapter introduces a different distributed strategy for solving them. In addition to presenting a review of distributed algorithms for perception in localization and map merging, the text also provides the reader with the necessary tools for proposing new solutions to problems of multi-robot perception, as well as other interesting topics related to multi-robot scenarios. The coverage is largely self-contained, supported by numerous explanations and demonstrations, although references for further study are also supplied. The reader will not require any prior background knowledge, other than a basic understanding of mathematics at a graduate-student level.
Download or read book CloudRobotics Distributed Robotics using Cloud Computing written by João Pedro Carvalho Rosa and published by University of Coimbra. This book was released on 2016-07-01 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cloud Computing is a paradigm shift in computation that has been gaining traction over the recent years, which is supported by the increasing availability and ubiquity of a reliable wireless connection to the Internet. Cloud Computing enables the access to seemingly unlimited computer resources that are located on an external computer cluster (the Cloud). In contrast, some robots, e.g. drones, have mobility requirements such as maximum size/weight or minimum autonomy, and carrying more onboard computer resources usually means hindering these requirements. This principle can be brought to the field of Robotics hence the name Cloud Robotics. In this case, the goal is to allow robots to perform tasks they would not be able to under normal circumstances and/or to free onboard resources so that more tasks or more complex tasks can be executed at the same time by a mobile robot. There are many existing robotic tasks that can take advantage of massive processing power and storage, such as simultaneous localization and mapping (SLAM), navigation and trajectory planning, image processing, pattern recognition, human-robot interaction and machine learning to name a few. All of these can quickly drain the robot out of its computer resources, especially if some of these tasks are running at the same time. However, in order to access and export data to the Cloud some bandwidth is needed, thus making the system a tradeoff: on the one hand, computation load and storage space is being freed, while on the other hand more strain is being put on the wireless network usage. As wireless connection protocols become more and more powerful, a Cloud-based solution becomes more interesting. This dissertation aims to analyse this tradeoff by adapting two existing multi-robot tasks, working on the Robotic Operating System (ROS), and compare the Cloud-based approach to the traditional one. To validate the capabilities of Cloud-based robotic systems, both simulations and experiments with real robots were conducted. Simulation results show a clear gain in CPU time, while the latter confirms the outcome of the tasks remains the same. Despite the Cloud-based systems, requiring considerably more bandwidth, a modern off-the-shelf Wi-Fi router can provide with enough to support any realistic team of robots.
Download or read book FastSLAM written by Michael Montemerlo and published by Springer Science & Business Media. This book was released on 2007-01-18 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph describes a new family of algorithms for the simultaneous localization and mapping (SLAM) problem in robotics, called FastSLAM. The FastSLAM-type algorithms have enabled robots to acquire maps of unprecedented size and accuracy, in a number of robot application domains and have been successfully applied in different dynamic environments, including a solution to the problem of people tracking.
Download or read book A Cooperative SLAM Framework with Efficient Information Sharing over Mobile Ad Hoc Networks written by Gonçalo dos Santos Martins and published by University of Coimbra. This book was released on 2014-07-01 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the cost of simple robotic platforms plummets, interest in solutions that explore the cooperation between robotic agents grows. Cooperative techniques enjoy a multitude of advantages over their individual counterparts, namely concerning the solution of easily divisible problems. Simultaneous Localization and Mapping (SLAM) is one of the most researched topics in Robotics. It deals with the problem of endowing a mobile robotic platform with the ability to, with no a priori knowledge of the environment, build a representation of its surroundings and, simultaneously, localize itself in it. The exploration of unknown environments seems to be a particularly and intuitively divisible problem, at least at a human level: we simply divide the team into smaller groups, or even into individuals, which explore different areas in the environment. After exploring, the team reassembles and builds a joint representation of the region. However, this approach gives rise to a new set of problems, such as communication, synchronization and information fusion. This work focuses in the solution of these problems, known collectively as Multi-Robot SLAM. We propose a novel software solution that seeks to provide any system capable of performing single robot SLAM with the ability to efficiently communicate with its teammates and to build a global representation of the environment based on the information it exchanges with its peers. This solution was validated through experiments conducted over real-world data, both on- and off-line, i.e., both using prerecorded and data gathered during the experiment. It has shown acceptable performance, both in scalability and communication efficiency.
Download or read book MRgraphSLAM Cooperative Graph Based SLAM with Efficient Information Sharing over Mobile Ad Hoc Networks written by Gonçalo dos Santos Martins and published by University of Coimbra. This book was released on 2013-12-01 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nothing provided
Download or read book Robot Localization and Map Building written by Hanafiah Yussof and published by BoD – Books on Demand. This book was released on 2010-03-01 with total page 589 pages. Available in PDF, EPUB and Kindle. Book excerpt: Localization and mapping are the essence of successful navigation in mobile platform technology. Localization is a fundamental task in order to achieve high levels of autonomy in robot navigation and robustness in vehicle positioning. Robot localization and mapping is commonly related to cartography, combining science, technique and computation to build a trajectory map that reality can be modelled in ways that communicate spatial information effectively. This book describes comprehensive introduction, theories and applications related to localization, positioning and map building in mobile robot and autonomous vehicle platforms. It is organized in twenty seven chapters. Each chapter is rich with different degrees of details and approaches, supported by unique and actual resources that make it possible for readers to explore and learn the up to date knowledge in robot navigation technology. Understanding the theory and principles described in this book requires a multidisciplinary background of robotics, nonlinear system, sensor network, network engineering, computer science, physics, etc.
Download or read book Reliable and Resource aware Collaborative SLAM for Multi robot Search and Rescue written by Yulun Tian and published by . This book was released on 2019 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: Collaborative simultaneous localization and mapping (CSLAM) is a core capability for many multi-robot systems operating in GPS-denied environments. Motivated by the application of forest search and rescue, this thesis presents two contributions that advance state-of-the-art CSLAM systems. The first part proposes a reliable loop closure procedure for the forest environment. Complex occlusions and strong perceptual aliasing often make it extremely difficult to detect previously visited areas. By leveraging stable tree features extracted from the environment, our approach significantly improves precision and recall during loop closure detection. The proposed technique is fully integrated into a centralized CSLAM system, and is extensively validated during real-world collaborative exploration missions in the forest. The second part of this thesis proposes a resource-aware framework for distributed loop closure detection in CSLAM. Detecting inter-robot loop closures is a resource-demanding process that involves exchanging observations and verifying potential matches. This poses severe challenges for mobile robots as they are frequently limited by available onboard resources. We propose a principled framework for robots to seamlessly adapt to such resource constraints while maximizing performance. Given budgets on computation and communication, our proposed method maximizes a task-oriented performance metric by selecting and verifying a budget-feasible set of potential loop closures. We show that this problem is NP-hard in general. Then, we provide simple approximation algorithms and leverage results on monotone submodular maximization to establish provable performance guarantees. The proposed framework is extensively evaluated on real and synthetic SLAM benchmarks.
Download or read book MHT based Multi robot Simultaneous Localization and Tracking written by 王紹丞 and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multi robot FastSLAM for Large Domains written by Choyong Koperski and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
