The Experts below are selected from a list of 148044 Experts worldwide ranked by ideXlab platform

Roland Siegwart - One of the best experts on this subject based on the ideXlab platform.

  • a review of point cloud registration algorithms for Mobile Robotics
    2015
    Co-Authors: Francois Pomerleau, Francis Colas, Roland Siegwart
    Abstract:

    The topic of this review is geometric registration in Robotics. Registrationalgorithms associate sets of data into a common coordinate system.They have been used extensively in object reconstruction, inspection,medical application, and localization of Mobile Robotics. We focus onMobile Robotics applications in which point clouds are to be registered.While the underlying principle of those algorithms is simple, manyvariations have been proposed for many different applications. In thisreview, we give a historical perspective of the registration problem andshow that the plethora of solutions can be organized and differentiatedaccording to a few elements. Accordingly, we present a formalizationof geometric registration and cast algorithms proposed in the literatureinto this framework. Finally, we review a few applications of thisframework in Mobile Robotics that cover different kinds of platforms,environments, and tasks. These examples allow us to study the specificrequirements of each use case and the necessary configuration choicesleading to the registration implementation. Ultimately, the objective ofthis review is to provide guidelines for the choice of geometric registrationconfiguration.

  • A Robust Descriptor for Tracking Vertical Lines in Omnidirectional Images and its Use in Mobile Robotics
    International Journal on Robotics Research, 2009
    Co-Authors: Davide Scaramuzza, Agostino Martinelli, Roland Siegwart
    Abstract:

    In this paper we introduce a robust descriptor for matching vertical lines among two or more images from an omnidirectional camera. Furthermore, in order to make such a descriptor usable in the framework of indoor Mobile Robotics, this paper introduces a new simple strategy to extrinsically self-calibrate the omnidirectional sensor with the odometry reference system. In the first part of this paper we describe how to build the feature descriptor.We show that the descriptor is very distinctive and is invariant to rotation and slight changes in illumination. The robustness of the descriptor is validated through real experiments on a wheeled robot. The second part of the paper is devoted to the extrinsic self-calibration of the camera with the odometry reference system. We show that by implementing an extended Kalman filter that fuses the information from the visual features with the odometry, it is possible to extrinsically and automatically calibrate the camera while the robot is moving. In particular, it is theoretically shown that only one feature suffices to perform the calibration. Experimental results validate the theoretical contributions.

  • a comparison of line extraction algorithms using 2d range data for indoor Mobile Robotics
    Autonomous Robots, 2007
    Co-Authors: Viet Hai Nguyen, Agostino Martinelli, N Tomatis, Stefan Gachter, Roland Siegwart
    Abstract:

    This paper presents an experimental evaluation of different line extraction algorithms applied to 2D laser scans for indoor environments. Six popular algorithms in Mobile Robotics and computer vision are selected and tested. Real scan data collected from two office environments by using different platforms are used in the experiments in order to evaluate the algorithms. Several comparison criteria are proposed and discussed to highlight the advantages and drawbacks of each algorithm, including speed, complexity, correctness and precision. The results of the algorithms are compared with ground truth using standard statistical methods. An extended case study is performed to further evaluate the algorithms in a SLAM application.

  • a comparison of line extraction algorithms using 2d laser rangefinder for indoor Mobile Robotics
    None, 2005
    Co-Authors: V T Nguyen, Agostino Martinelli, N Tomatis, Roland Siegwart
    Abstract:

    This paper presents an experimental evaluation of different line extraction algorithms on 2D laser scans for indoor environment. Six popular algorithms in Mobile Robotics and computer vision are selected and tested. Experiments are performed on $mathbf{100}$ real data scans collected in an office environment with a map size of $mathbf{80m times 50m}$. Several comparison criteria are proposed and discussed to highlight the advantages and drawbacks of each algorithm, including speed, complexity, correctness and precision. The results of the algorithms are compared with the ground truth using standard statistical methods.

  • introduction to autonomous Mobile robots
    2004
    Co-Authors: Roland Siegwart, Illah Nourbakhsh, Davide Scaramuzza
    Abstract:

    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.

Dehann Fourie - One of the best experts on this subject based on the ideXlab platform.

  • slamindb centralized graph databases for Mobile Robotics
    International Conference on Robotics and Automation, 2017
    Co-Authors: Dehann Fourie, Roxana Mata, Sudeep Pillai, Samuel Claassens, John J Leonard
    Abstract:

    Robotic systems typically require memory recall mechanisms for a variety of tasks including localization, mapping, planning, visualization etc. We argue for a novel memory recall framework that enables more complex inference schemas by separating the computation from its associated data. In this work we propose a shared, centralized data persistence layer that maintains an ensemble of online, situationally-aware robot states. This is realized through a queryable graph-database with an accompanying key-value store for larger data. In turn, this approach is scalable and enables a multitude of capabilities such as experience-based learning and long-term autonomy. Using multi-modal simultaneous localization and mapping and a few example use-cases, we demonstrate the versatility and extensible nature that centralized persistence and SLAMinDB can provide. In order to support the notion of life-long autonomy, we envision robots to be endowed with such a persistence model, enabling them to revisit previous experiences and improve upon their existing task-specific capabilities.

  • SLAMinDB: Centralized graph databases for Mobile Robotics
    Proceedings - IEEE International Conference on Robotics and Automation, 2017
    Co-Authors: Dehann Fourie, Roxana Mata, Sudeep Pillai, Samuel Claassens, John Leonard
    Abstract:

    — Robotic systems typically require memory recall mechanisms for a variety of tasks including localiza-tion, mapping, planning, visualization etc. We argue for a novel memory recall framework that enables more complex inference schemas by separating the computation from its associated data. In this work we propose a shared, cen-tralized data persistence layer that maintains an ensemble of online, situationally-aware robot states. This is realized through a queryable graph-database with an accompanying key-value store for larger data. In turn, this approach is scalable and enables a multitude of capabilities such as experience-based learning and long-term autonomy. Using multi-modal simultaneous localization and mapping and a few example use-cases, we demonstrate the versatility and extensible nature that centralized persistence and SLAMinDB can provide. In order to support the notion of life-long autonomy, we envision robots to be endowed with such a persistence model, enabling them to revisit previous experiences and improve upon their existing task-specific capabilities. I. IIII Realizing tangible value from robotic data requires a versatile and highly-accessible data representation. Novel database technologies provide advantages in representation, manipulation, and extraction. We argue the benefits of graph databases in Robotics by exploring spatio-temporal representation and centralized persis-tence. This enables situationally-aware querying and inference of the robot's task-specific state at any point in its history. We view this as a critical component in the robot's ability to learn newer representations from previous experiences. We propose a two-tier persistence architecture as depicted in Fig. 1 that maintains independent databases for: (i) A graph that provides both the master data index as well a store for relational, queryable data (e.g. the robot's Maximum-A-Posteriori state estimate); (ii) A key-value store retaining arbitrarily large sensor data (e.g. RGB and Depth (RGB-D) imagery and laser scans). Through potential use-cases and experiments, we emphasize the flexibility of graph databases for a mul-titude of concurrent tasks: (i) Post-hoc loop closure *Equal contributors, dehann@csail.mit.edu is with the Joint

Volkan Isler - One of the best experts on this subject based on the ideXlab platform.

  • search and pursuit evasion in Mobile Robotics
    Autonomous Robots, 2011
    Co-Authors: Timothy H. Chung, Geoffrey A. Hollinger, Volkan Isler
    Abstract:

    This paper surveys recent results in pursuit-evasion and autonomous search relevant to applications in Mobile Robotics. We provide a taxonomy of search problems that highlights the differences resulting from varying assumptions on the searchers, targets, and the environment. We then list a number of fundamental results in the areas of pursuit-evasion and probabilistic search, and we discuss field implementations on Mobile robotic systems. In addition, we highlight current open problems in the area and explore avenues for future work.

  • Search and pursuit-evasion in Mobile Robotics A survey
    Autonomous Robots, 2011
    Co-Authors: Timothy H. Chung, Geoffrey A. Hollinger, Volkan Isler
    Abstract:

    This paper surveys recent results in pursuit-evasion and autonomous search relevant to applications in Mobile Robotics. We provide a taxonomy of search prob-lems that highlights the differences resulting from varying assumptions on the searchers, targets, and the environment. We then list a number of fundamental results in the areas of pursuit-evasion and probabilistic search, and we discuss field implementations on Mobile robotic systems. In addi-tion, we highlight current open problems in the area and explore avenues for future work.

Ulrich Nehmzow - One of the best experts on this subject based on the ideXlab platform.

  • Mobile Robotics: Research, Applications and Challenges
    2020
    Co-Authors: Ulrich Nehmzow
    Abstract:

    This overview paper discusses some of the major focuses of current Mobile Robotics research, introduces a specic application of Mobile Robotics | automated inspection using autonomous novelty detection | and presents one of the future challenges of Mobile Robotics research: that of applying quantitative methods in Mobile Robotics, in order to change the discipline from an empirical one to a more precise science.

  • scientific methods in Mobile Robotics quantitative analysis of agent behaviour
    2006
    Co-Authors: Ulrich Nehmzow
    Abstract:

    A Brief Introduction to Mobile Robotics Introduction to Scientific Methods in Mobile Robotics Statistical Tools for Describing Experimental Data Dynamical Systems Theory and Agent Behaviour Analysis of Agent Behaviour - Case Studies Computer Modelling of Robot-Environment Interaction Conclusion

  • Scientific methods in Mobile Robotics: Quantitative analysis of agent behaviour
    Scientific Methods in Mobile Robotics: Quantitative Analysis of Agent Behaviour, 2006
    Co-Authors: Ulrich Nehmzow
    Abstract:

    Mobile Robotics is a cutting-edge research topic, which until recently has primarily focused on issues such as the design of controllers and robot hardware. The field is now ready to embrace theoretical methods from dynamical systems theory, statistics and system identification to produce quantitative analyses and computer models of robot-environment interaction. _Scientific Methods in Mobile Robotics: Quantitative Analysis of Agent Behaviour_ is a decisive step towards a theoretical understanding of the operation of autonomous Mobile Robotics. This book presents cutting-edge research results on the application of chaos theory, parametric and non- parametric statistics and dynamical systems theory in Mobile Robotics. It presents foundations of a theory of Mobile Robotics by providing a quantitative analysis of the interaction between robot, task and environment. Practical examples and case studies show how robot behaviour can be logged, modelled, analysed and interpreted. This new approach will aid the design of controllers, analysis of agent behaviour and the verification of experimental results. As the first book to apply advanced scientific methods to the growing field of Mobile robots, _Scientific Methods in Mobile Robotics: Quantitative Analysis of Agent Behaviour_ will interest researchers, lecturers and post-graduate students in Robotics, artificial intelligence and cognitive science.

  • Mobile Robotics: A Practical Introduction - Mobile Robotics: A Practical Introduction
    2003
    Co-Authors: Ulrich Nehmzow
    Abstract:

    From the Publisher: Mobile Robotics: A Practical Introduction is an excellent introduction to the foundations and methods used for designing completely autonomous Mobile robots. A fascinating, cutting-edge research topic, autonomous Mobile Robotics is now taught in more and more universities. In this book you are introduced to the fundamental concepts of this complex field via twelve detailed case studies which show how to build and program real working robots. Topics covered include learning, autonomous navigation in unmodified, noisy and unpredictable environments, and high fidelity Mobile robot simulation. This book provides a very practical introduction to Mobile Robotics for a general scientific audience, and is essential reading for final year undergraduate students and postgraduate students studying Robotics, Artificial Intelligence, Cognitive Science and Robot Engineering. Its update and overview of core concepts in Mobile Robotics will assist and encourage practitioners of the field, and set challenges to explore new avenues of research in this exciting field.

  • Mobile Robotics a practical introduction
    2003
    Co-Authors: Ulrich Nehmzow
    Abstract:

    From the Publisher: Mobile Robotics: A Practical Introduction is an excellent introduction to the foundations and methods used for designing completely autonomous Mobile robots. A fascinating, cutting-edge research topic, autonomous Mobile Robotics is now taught in more and more universities. In this book you are introduced to the fundamental concepts of this complex field via twelve detailed case studies which show how to build and program real working robots. Topics covered include learning, autonomous navigation in unmodified, noisy and unpredictable environments, and high fidelity Mobile robot simulation. This book provides a very practical introduction to Mobile Robotics for a general scientific audience, and is essential reading for final year undergraduate students and postgraduate students studying Robotics, Artificial Intelligence, Cognitive Science and Robot Engineering. Its update and overview of core concepts in Mobile Robotics will assist and encourage practitioners of the field, and set challenges to explore new avenues of research in this exciting field.

Jorge Casillas - One of the best experts on this subject based on the ideXlab platform.

  • a case study for learning behaviors in Mobile Robotics by evolutionary fuzzy systems
    Expert Systems With Applications, 2010
    Co-Authors: Manuel Mucientes, Jesus Alcalafdez, Rafael Alcala, Jorge Casillas
    Abstract:

    Service robots will play an increasing and more important role in the society in the next years. One of the main challenges is to endow robots with enough autonomy to operate on real environments. To reach that goal, the design of controllers to solve simple tasks must be automatized. Engineers look for learning algorithms that are general, robust, require low expertise knowledge, and generate controllers that can run on the real robot without any tuning stage. In this paper, a framework to learn behaviors (controllers) in Mobile Robotics, fulfilling the previous requirements, has been used. The framework is based on two modules: dataset generation and a data-driven evolutionary-based learning algorithm to obtain fuzzy controllers. Nevertheless, the design of a fuzzy controller still requires the selection of the type of learning algorithm, and also to choose the value of some design parameters. In this paper we present an exhaustive study on a set of evolutionary-based data-driven learning algorithms, for learning fuzzy controllers in Mobile Robotics, that cover a wide range of the accuracy/interpretability trade-off. The study has also evaluated the influence of the values of all the design parameters over accuracy and interpretability. The objective is to analyze the performance of the different algorithms for the design of behaviors in Mobile Robotics, and to extract some general rules that can help in the process to design new behaviors. The analysis comprises two different behaviors (wall-following and moving object following) and more than 450 tests, both in simulation and on a Pioneer II AT robot. Results have shown very good performances in complex and realistic conditions for the different combinations of algorithms and parameters.

  • quick design of fuzzy controllers with good interpretability in Mobile Robotics
    IEEE Transactions on Fuzzy Systems, 2007
    Co-Authors: Manuel Mucientes, Jorge Casillas
    Abstract:

    This paper presents a methodology for the design of fuzzy controllers with good interpretability in Mobile Robotics. It is composed of a technique to automatically generate a training data set plus an efficient algorithm to learn fuzzy controllers. The proposed approach obtains a highly interpretable knowledge base in a very reduced time, and the designer only has to define the number of membership functions and the universe of discourse of each variable, together with a scoring function. In addition, the learned fuzzy controllers are general because the training set is composed of a number of automatically generated examples that cover the universe of discourse of each variable uniformly and with a predefined precision. The methodology has been applied to the design of a wall-following and moving object following behavior. Several tests in simulated environments using the Nomad 200 robot software and a comparison with another learning method show the performance and advantages of the proposed approach.