The Experts below are selected from a list of 22842 Experts worldwide ranked by ideXlab platform

Yangsheng Xu - One of the best experts on this subject based on the ideXlab platform.

  • Learning Human Navigational Skill for Smart Wheelchair in a Static Cluttered Route
    IEEE Transactions on Industrial Electronics, 2006
    Co-Authors: Hon Nin Chow, Yangsheng Xu
    Abstract:

    In practice, the environments in which mobile robots operate are usually modeled in highly complex forms and, as a result, autonomous navigation and localization can be difficult. The difficulties are exacerbated for practical robots with limited on-board computational resources and complex planning algorithms, since this paradigm of Environmental Modeling requires enormous computational power. A novel navigation/localization learning methodology is presented to abstract and transfer the human sequential navigational skill to a robotic wheelchair by showing the platform how to respond in different local environments along a demonstrated, static cluttered route using a lookup table representation. This method utilizes limited on-board range sensing information to concisely model local unstructured environments, with respect to the robot, for navigation or localization along the learned route in order to achieve good performance with low on-line computational demand and low-cost hardware requirements. Experimental study demonstrates the feasibility of this method and some interesting characteristics of navigation, localization, and Environmental Modeling problems. Analysis is also conducted to investigate performance evaluation, advantages of the approach, choices of lookup table inputs and outputs, and potential generalization of this paper

  • Learning human navigational skill for smart wheelchair
    IEEE RSJ International Conference on Intelligent Robots and Systems, 2002
    Co-Authors: Hon Nin Chow, Yangsheng Xu
    Abstract:

    In practice, the environments in which mobile robots operate are usually modeled in highly complex geometric representations, and as a result real-time autonomous navigation can be difficult. Such difficulty is even exacerbated for robots with limited but more realistic on-board computational resources since this paradigm of Environmental Modeling requires enormous computational power. Inspired from human daily life experience, we propose in this paper a new direction for practical robotics navigation system with locally sensed non-geometric Environmental Modeling. With human-guided demonstrations, the robot can learn and abstract human navigational skill in the form of reactive sensor-motor mapping to navigate in the demonstrated route with simultaneous obstacle avoidance, localization, path and trajectory planning. Learning in a cascade neural network with node-decoupled extended Kalman filtering is adopted as the basis for such reactive mapping. Preliminarily experimental results show the feasibility of this practical approach.

Alex Otto - One of the best experts on this subject based on the ideXlab platform.

  • geospace Environmental Modeling gem magnetic reconnection challenge
    Journal of Geophysical Research, 2001
    Co-Authors: J. Birn, J. F. Drake, M. A. Shay, B. N. Rogers, R. E. Denton, MATTHIAS HESSE, Anirban Bhattacharjee, M M Kuznetsova, Z W, Alex Otto
    Abstract:

    The Geospace Environmental Modeling (GEM) Reconnection Challenge project is presented and the important results, which are presented in a series of companion papers, are summarized. Magnetic reconnection is studied in a simple Harris sheet configuration with a specified set of initial conditions, including a finite amplitude, magnetic island perturbation to trigger the dynamics. The evolution of the system is explored with a broad variety of codes, ranging from fully electromagnetic particle in cell (PIC) codes to conventional resistive magnetohydrodynamic (MHD) codes, and the results are compared. The goal is to identify the essential physics which is required to model collisionless magnetic reconnection. All models that include the Hall effect in the generalized Ohm's law produce essentially indistinguishable rates of reconnection, corresponding to nearly Alfvenic inflow velocities. Thus the rate of reconnection is insensitive to the specific mechanism which breaks the frozen-in condition, whether resistivity, electron inertia, or electron thermal motion. The reconnection rate in the conventional resistive MHD model, in contrast, is dramatically smaller unless a large localized or current dependent resistivity is used. The Hall term brings the dynamics of whistler waves into the system. The quadratic dispersion property of whistlers (higher phase speed at smaller spatial scales) is the key to understanding these results. The implications of these results for trying to model the global dynamics of the magnetosphere are discussed.

  • Geospace Environmental Modeling (GEM) Magnetic Reconnection Challenge
    Journal of Geophysical Research: Space Physics, 2001
    Co-Authors: J. Birn, J. F. Drake, M. A. Shay, B. N. Rogers, R. E. Denton, MATTHIAS HESSE, M. Kuznetsova, Z. W. Ma, Anirban Bhattacharjee, Alex Otto
    Abstract:

    The Geospace Environmental Modeling (GEM) Reconnection Challenge project is presented and the important results, which are presented in a series of companion papers, are summarized. Magnetic reconnection is studied in a simple Harris sheet configuration with a specified set of initial conditions, including a finite amplitude, magnetic island perturbation to trigger the dynamics. The evolution of the system is explored with a broad variety of codes, ranging from fully electromagnetic particle in cell (PIC) codes to conventional resistive magnetohydrodynamic (MHD) codes, and the results are compared. The goal is to identify the essential physics which is required to model collisionless magnetic reconnection. All models that include the Hall effect in the generalized Ohm's law produce essentially indistinguishable rates of reconnection, corresponding to nearly Alfvénic inflow velocities. Thus the rate of reconnection is insensitive to the specific mechanism which breaks the frozen-in condition, whether resistivity, electron inertia, or electron thermal motion. The reconnection rate in the conventional resistive MHD model, in contrast, is dramatically smaller unless a large localized or current dependent resistivity is used. The Hall term brings the dynamics of whistler waves into the system. The quadratic dispersion property of whistlers (higher phase speed at smaller spatial scales) is the key to understanding these results. The implications of these results for trying to model the global dynamics of the magnetosphere are discussed.

Hon Nin Chow - One of the best experts on this subject based on the ideXlab platform.

  • Learning Human Navigational Skill for Smart Wheelchair in a Static Cluttered Route
    IEEE Transactions on Industrial Electronics, 2006
    Co-Authors: Hon Nin Chow, Yangsheng Xu
    Abstract:

    In practice, the environments in which mobile robots operate are usually modeled in highly complex forms and, as a result, autonomous navigation and localization can be difficult. The difficulties are exacerbated for practical robots with limited on-board computational resources and complex planning algorithms, since this paradigm of Environmental Modeling requires enormous computational power. A novel navigation/localization learning methodology is presented to abstract and transfer the human sequential navigational skill to a robotic wheelchair by showing the platform how to respond in different local environments along a demonstrated, static cluttered route using a lookup table representation. This method utilizes limited on-board range sensing information to concisely model local unstructured environments, with respect to the robot, for navigation or localization along the learned route in order to achieve good performance with low on-line computational demand and low-cost hardware requirements. Experimental study demonstrates the feasibility of this method and some interesting characteristics of navigation, localization, and Environmental Modeling problems. Analysis is also conducted to investigate performance evaluation, advantages of the approach, choices of lookup table inputs and outputs, and potential generalization of this paper

  • Learning human navigational skill for smart wheelchair
    IEEE RSJ International Conference on Intelligent Robots and Systems, 2002
    Co-Authors: Hon Nin Chow, Yangsheng Xu
    Abstract:

    In practice, the environments in which mobile robots operate are usually modeled in highly complex geometric representations, and as a result real-time autonomous navigation can be difficult. Such difficulty is even exacerbated for robots with limited but more realistic on-board computational resources since this paradigm of Environmental Modeling requires enormous computational power. Inspired from human daily life experience, we propose in this paper a new direction for practical robotics navigation system with locally sensed non-geometric Environmental Modeling. With human-guided demonstrations, the robot can learn and abstract human navigational skill in the form of reactive sensor-motor mapping to navigate in the demonstrated route with simultaneous obstacle avoidance, localization, path and trajectory planning. Learning in a cascade neural network with node-decoupled extended Kalman filtering is adopted as the basis for such reactive mapping. Preliminarily experimental results show the feasibility of this practical approach.

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

  • Topological global localization and mapping with fingerprints and uncertainty
    Springer Tracts in Advanced Robotics, 2006
    Co-Authors: Adriana Tapus, Nicola Tomatis, Roland Siegwart
    Abstract:

    Navigation in unknown or partially unknown environments remains one of the biggest challenges in today's mobile robotics. Environmental Modeling, perception, localization and mapping are all needed for a successful approach. The contribution of this paper resides in the extension of the fingerprint concept (circular list of features around the robot) with uncertainty Modeling, in order to improve localization and allow for automatic map building. The uncertainty is defined as the probability of a feature of being present in the environment when the robot perceives it. The whole approach is presented in details and viewed in a topological optic. Experimental results of the perception and localization capabilities with a mobile robot equipped with two 180 degrees laser range finders and an onmi-directional camera are reported.

  • Environmental Modeling with fingerprint sequences for topological global localization
    Proceedings 2003 IEEE RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453), 2003
    Co-Authors: P. Lamon, Adriana Tapus, Nicola Tomatis, E. Glauser, Roland Siegwart
    Abstract:

    In this paper a perception approach allowing for high distinctiveness is presented. The method works in accordance to the fingerprint concept. Such representation allows using a very flexible matching approach based on the minimum energy algorithm. The whole extraction and matching approach is presented in details and viewed in a topological optic, where the matching result can directly be used as observation function for a topological localization approach. The experimentation section will validate the fingerprint approach and present different set of experiments in order to explain practically the choice of different types of features.

Laj R. Ahuja - One of the best experts on this subject based on the ideXlab platform.

  • a software engineering perspective on Environmental Modeling framework design
    Environmental Modelling and Software, 2013
    Co-Authors: Olaf David, G. H. Leavesley, J. C. Ascough, Wes Lloyd, Ken Rojas, Timothy R. Green, Laj R. Ahuja
    Abstract:

    The Environmental Modeling community has historically been concerned with the proliferation of models and the effort associated with collective model development tasks (e.g., code generation, data transformation, etc.). Environmental Modeling frameworks (EMFs) have been developed to address this problem, but much work remains before EMFs are adopted as mainstream Modeling tools. Environmental model development requires both scientific understanding of Environmental phenomena and software developer proficiency. EMFs support the Modeling process through streamlining model code development, allowing seamless access to data, and supporting data analysis and visualization. EMFs also support aggregation of model components into functional units, component interaction and communication, temporal-spatial stepping, scaling of spatial data, multi-threading/multi-processor support, and cross-language interoperability. Some EMFs additionally focus on high-performance computing and are tailored for particular Modeling domains such as ecosystem, socio-economic, or climate change research. The Object Modeling System Version 3 (OMS3) EMF employs new advances in software framework design to better support the Environmental model development process. This paper discusses key EMF design goals/constraints and addresses software engineering aspects that have made OMS3 framework development efficacious and its application practical, as demonstrated by leveraging software engineering efforts outside of the Modeling community and lessons learned from over a decade of EMF development. Software engineering approaches employed in OMS3 are highlighted including a non-invasive lightweight framework design supporting component-based model development, use of implicit parallelism in system design, use of domain specific language design patterns, and cloud-based support for computational scalability. The key advancements in EMF design presented herein may be applicable and beneficial for other EMF developers seeking to better support Environmental model development through improved framework design.

  • Environmental Modeling framework invasiveness: Analysis and implications
    Environmental Modelling and Software, 2011
    Co-Authors: Wes Lloyd, G. H. Leavesley, J. C. Ascough, Olaf David, Ken Rojas, J. R. Carlson, Peter Krause, Timothy R. Green, Laj R. Ahuja
    Abstract:

    Environmental Modeling frameworks support scientific model development by providing model developers with domain specific software libraries which are used to aid model implementation. This paper presents an investigation on the framework invasiveness of Environmental Modeling frameworks. Invasiveness, similar to object-oriented coupling, is defined as the quantity of dependencies between model code and a Modeling framework. We investigated relationships between invasiveness and the quality of Modeling code, and also the utility of using a lightweight framework design approach in an Environmental Modeling framework. Five metrics to measure framework invasiveness were proposed and applied to measure dependencies between model and framework code of several implementations of Thornthwaite and the Precipitation-Runoff Modeling System (PRMS), two well-known hydrological models. Framework invasiveness measures were compared with existing common software metrics including size (lines of code), cyclomatic complexity, and object-oriented coupling. Models with lower framework invasiveness tended to be smaller, less complex, and have less coupling. In addition, the lightweight framework implementations of the Thornthwaite and PRMS models were less invasive than the traditional framework model implementations. Our results show that model implementations with higher degrees of framework invasiveness also had structural characteristics which previously have been shown to predict poor maintainability, a non-functional code quality attribute of concern. We conclude that using a framework with a lightweight framework design shows promise in helping to improve the quality of model code and that the lightweight framework design approach merits further attention by Environmental Modeling framework developers.