The Experts below are selected from a list of 45 Experts worldwide ranked by ideXlab platform

Yu Zhou - One of the best experts on this subject based on the ideXlab platform.

  • IROS - Recovering the position and orientation of a mobile robot from a single image of identified landmarks
    2007 IEEE RSJ International Conference on Intelligent Robots and Systems, 2007
    Co-Authors: Yu Zhou
    Abstract:

    This paper introduces a novel self-localization algorithm for mobile robots, which recovers the robot position and orientation from a single image of identified landmarks taken by an onboard camera. The visual angle between two landmarks can be derived from their projections in the same image. The distances between the optical center and the landmarks can be calculated from the visual angles and the known landmark positions based on the Law of Cosine. The robot position can be determined using the principle of trilateration. The robot orientation is then computed from the robot position, landmark positions and their projections. Extensive simulation has been carried out. A comprehensive error analysis provides the insight on how to improve the localization accuracy.

  • Robot Self-Localization based on a Single Image of Identified Landmarks
    2007 International Symposium on Computational Intelligence in Robotics and Automation, 2007
    Co-Authors: Yu Zhou
    Abstract:

    This paper introduces a novel self-localization algorithm for mobile robots, which recovers the robot position from a single image of identified landmarks taken by an onboard camera. The visual angle between two landmarks can be derived from their projections in the same image. The distances between the optical center and the landmarks can be calculated from the visual angles and the known landmark positions based on the Law of Cosine. The robot position can then be determined using the principle of trilateration. Extensive simulation has been carried out. A comprehensive error analysis provides the insight on how to improve the localization accuracy.

  • CIRA - Robot Self-Localization based on a Single Image of Identified Landmarks
    2007 International Symposium on Computational Intelligence in Robotics and Automation, 2007
    Co-Authors: Yu Zhou
    Abstract:

    This paper introduces a novel self-localization algorithm for mobile robots, which recovers the robot position from a single image of identified landmarks taken by an onboard camera. The visual angle between two landmarks can be derived from their projections in the same image. The distances between the optical center and the landmarks can be calculated from the visual angles and the known landmark positions based on the Law of Cosine. The robot position can then be determined using the principle of trilateration. Extensive simulation has been carried out. A comprehensive error analysis provides the insight on how to improve the localization accuracy.

  • Recovering the position and orientation of a mobile robot from a single image of identified landmarks
    2007 IEEE RSJ International Conference on Intelligent Robots and Systems, 2007
    Co-Authors: Yu Zhou
    Abstract:

    This paper introduces a novel self-localization algorithm for mobile robots, which recovers the robot position and orientation from a single image of identified landmarks taken by an onboard camera. The visual angle between two landmarks can be derived from their projections in the same image. The distances between the optical center and the landmarks can be calculated from the visual angles and the known landmark positions based on the Law of Cosine. The robot position can be determined using the principle of trilateration. The robot orientation is then computed from the robot position, landmark positions and their projections. Extensive simulation has been carried out. A comprehensive error analysis provides the insight on how to improve the localization accuracy.

Sung-bong Yang - One of the best experts on this subject based on the ideXlab platform.

  • An Effective Bump Mapping Hardware Architecture Using Polar Coordinate System
    Journal of Information Science and Engineering, 2007
    Co-Authors: Woo-chan Park, Sung-bong Yang
    Abstract:

    Bump mapping is a technique that represents the detailed parts of an object surface, such as the skin of a peanut, using the geometry mapping without complex modeling. However, the hardware implementation for bump mapping is very expensive, because a large amount of per pixel computations, including the normal vector shading, is required. In this paper, we propose an effective bump mapping algorithm that utilizes the reference space with the polar coordinate system and also propose a new hardware architecture associated with the proposed bump mapping algorithm. The proposed architecture reduces the computations to transform the vectors from the object space into the reference space by using a new vector rotation method. It also reduces the computations for the illumination calculation by using the Law of Cosine. Compared with the previous approaches, the proposed architecture reduces multiplication operations up to 78%.

  • Graphics Hardware - An effective hardware architecture for bump mapping using angular operation
    2003
    Co-Authors: Woo-chan Park, Sung-bong Yang
    Abstract:

    In this paper, we propose an effective bump mapping algorithm that utilizes the reference space with the polar coordinate system and also propose a new hardware architecture associated with the proposed bump mapping algorithm. The proposed architecture reduces the computations to transform the vectors from the object space into the reference space by using a new vector rotation method. It also reduces the computations for the illumination calculation by using the Law of Cosine. Compared with the previous approaches, the proposed architecture reduces multiplication operations up to 78%.

Seramika Ariwahjoedi - One of the best experts on this subject based on the ideXlab platform.

  • Contracted Bianchi Identity and Angle Relation on n-dimensional Simplicial Complex of Regge Calculus
    arXiv: General Relativity and Quantum Cosmology, 2018
    Co-Authors: Seramika Ariwahjoedi
    Abstract:

    In this article, we prove the theorems concerning the trace relation of SO(3), SU(2), and SO(n) which are representation of SO(3) and SU(2). An interesting fact we found is the trace relation of SU(2) gives the spherical Law of Cosine which in turns is a dihedral angle relation, a constraint that must be satisfied by closed Euclidean simplices. Moreover, we applied our results on general group elements to holonomies on the simplicial complex of Regge Calculus, which is the main motivation of this article. Here, we found that: (1) in 4-dimensional Euclidean Regge Gravity, all the holonomy circling a single hinge are simple rotations, and (2) the dihedral angle relation represents the 'contracted' Bianchi identity for a simplicial complex.

  • (2+1) Regge Calculus: Discrete Curvatures, Bianchi Identity, and Gauss-Codazzi Equation
    arXiv: General Relativity and Quantum Cosmology, 2017
    Co-Authors: Seramika Ariwahjoedi
    Abstract:

    The first results presented in our article are the clear definitions of both intrinsic and extrinsic discrete curvatures in terms of holonomy and plane-angle representation, a clear relation with their deficit angles, and their clear geometrical interpretations in the first order discrete geometry. The second results are the discrete version of Bianchi identity and Gauss-Codazzi equation, together with their geometrical interpretations. It turns out that the discrete Bianchi identity and Gauss-Codazzi equation, at least in 3-dimension, could be derived from the dihedral angle formula of a tetrahedron, while the dihedral angle relation itself is the spherical Law of Cosine in disguise. Furthermore, the continuous infinitesimal curvature 2-form, the standard Bianchi identity, and Gauss-Codazzi equation could be recovered in the continuum limit.

Woo-chan Park - One of the best experts on this subject based on the ideXlab platform.

  • An Effective Bump Mapping Hardware Architecture Using Polar Coordinate System
    Journal of Information Science and Engineering, 2007
    Co-Authors: Woo-chan Park, Sung-bong Yang
    Abstract:

    Bump mapping is a technique that represents the detailed parts of an object surface, such as the skin of a peanut, using the geometry mapping without complex modeling. However, the hardware implementation for bump mapping is very expensive, because a large amount of per pixel computations, including the normal vector shading, is required. In this paper, we propose an effective bump mapping algorithm that utilizes the reference space with the polar coordinate system and also propose a new hardware architecture associated with the proposed bump mapping algorithm. The proposed architecture reduces the computations to transform the vectors from the object space into the reference space by using a new vector rotation method. It also reduces the computations for the illumination calculation by using the Law of Cosine. Compared with the previous approaches, the proposed architecture reduces multiplication operations up to 78%.

  • Graphics Hardware - An effective hardware architecture for bump mapping using angular operation
    2003
    Co-Authors: Woo-chan Park, Sung-bong Yang
    Abstract:

    In this paper, we propose an effective bump mapping algorithm that utilizes the reference space with the polar coordinate system and also propose a new hardware architecture associated with the proposed bump mapping algorithm. The proposed architecture reduces the computations to transform the vectors from the object space into the reference space by using a new vector rotation method. It also reduces the computations for the illumination calculation by using the Law of Cosine. Compared with the previous approaches, the proposed architecture reduces multiplication operations up to 78%.

Hari Krishna Garg - One of the best experts on this subject based on the ideXlab platform.

  • Calibration-Free Indoor Positioning Using Crowdsourced Data and Multidimensional Scaling
    IEEE Transactions on Wireless Communications, 2020
    Co-Authors: Yonghao Zhao, Wai-choong Wong, Tianyi Feng, Hari Krishna Garg
    Abstract:

    Indoor positioning plays an important role in various location-based services (LBSs). In conventional systems, the process of constructing radio maps for positioning usually involves labor-intensive manual calibrations, which seriously limits the system's scalability and adaptiveness. In this paper, we propose an efficient calibration-free method by leveraging on crowdsourced WiFi signal data that are captured passively through a WiFi sensing testbed. Since the ground truths of the crowdsourced data are unavailable, the radio maps cannot be directly constructed. In the proposed method, we adopt the multidimensional scaling (MDS) technique to compute the positions of the unlabeled data thereby generating radio maps. In order to enable MDS, we estimate the pairwise distances among the unlabeled data by using an improved trilateration method and a Law of Cosine (LoC)-based geometrical algorithm without online pairwise measurements. Experimental results show that the accuracy of the proposed method is higher than trilateration-based method and reasonably lower than that of calibration-based method. Meanwhile, the run time of the proposed method is shorter than previous optimization-based methods. The short run time allows the radio maps to be dynamically updated against the environmental variations.