Self-localization of a Mobile Robot by Local Map Matching Using Fuzzy Logic.
ABSTRACT Reliable localization is a fundamental issue in robot navigation techniques. This paper describes an apporach for realizing
self-localization of mobile robot by matching the local map generated from a 2D laser scanner. Environment map is represented
by occupancy grids and it fuses the information of the robot’s pose using dead-reckoning method and the range to obstacles
by laser scanner using maximum likehood estimation. After a current laser scan, the positon of mobile robot, in relation to
a previous scan and pose estimates, is computed by matching the local map using fuzzy logic method. The effectiveness of this
method is demonstrated by experiments.
- SourceAvailable from: psu.edu[Show abstract] [Hide abstract]
ABSTRACT: Exact knowledge of the position of a vehicle is a fundamental problem in mobile robot applications. In search for a solution, researchers and engineers have developed a variety of systems, sensors, and techniques for mobile robot positioning. This paper provides a review of relevant mobile robot positioning technologies. The paper defines seven categories for positioning systems: 1. Odometry; 2. Inertial Navigation; 3. Magnetic Compasses; 4. Active Beacons; 5. Global Positioning Systems; 6. Landmark Navigation; and 7. Model Matching. The characteristics of each category are discussed and examples of existing technologies are given for each category. The field of mobile robot navigation is active and vibrant, with more great systems and ideas being developed continuously. For this reason the examples presented in this paper serve only to represent their respective categories, but they do not represent a judgment by the authors. Many ingenious approaches can be found in the literature, although, for reasons of brevity, not all could be cited in this paper. 1) (Corresponding Author) The University of Michigan, Advanced Technologies Lab, 1101 Beal Avenue, Ann Arbor, MI 48109-2110, Ph.: 313-763-1560, Fax: 313-944-1113. Email: email@example.com 2) Naval Command, Control, and Ocean Surveillance Center, RDT&E Division 5303, 271 Catalina Boulevard, San Diego, CA 92152-5001, Email: Everett@NOSC.MIL 3) The University of Michigan, Advanced Technologies Lab, 1101 Beal Avenue, Ann Arbor, MI 481092110, Email: Feng@engin.umich.edu 4) The University of Michigan, Dept. of Nuclear Engineering and Radiological Sciences, 239 Cooley Bldg., Ann Arbor, MI 48109, Email: firstname.lastname@example.org 2 1.
Conference Paper: Maximum likelihood rover localization by matching range maps[Show abstract] [Hide abstract]
ABSTRACT: This paper describes maximum likelihood estimation techniques for performing rover localization in natural terrain by matching range maps. An occupancy map of the local terrain is first generated using stereo vision. The position of the rover with respect to a previously generated occupancy map is then computed by comparing the maps using a probabilistic formulation of image matching techniques. Our motivation for this work is the desire for greater autonomy in Mars rovers. These techniques have been applied to data obtained from the Sojourner Mars rover and run on-board the Rocky 7 Mars rover prototypeRobotics and Automation, 1998. Proceedings. 1998 IEEE International Conference on; 06/1998