: Exact knowledge of the position of a vehicle is a fundamental problem in mobile robot applications. In the 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; 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. The appendix contains a tabular comparison of the positioning systems discussed in this review that includes system and description, features, accuracy (position), accuracy (orientation), effective range, and source of information. (47 refs.)

/pdf/mobile-robot-positioning-sensors-and-techniques-10qidh8m54.pdf

Mobile Robot Positioning - Sensors and Techniques

A closed-form analytical solution to the problem of 3D estimation of circular-feature location is presented. Two different cases are considered: 3D orientation and position estimation when the radius is known and when it is not known. Extension of the method to general 3D quadratic features is also addressed. Simulated experimental results obtained for all three cases verified the analytical method. In the case of real experiments, a set of circles located on a calibration plate, whose locations were known with respect to a reference frame, were used for camera calibration as well as for the application of the method. A sequential compensation procedure was applied to the input gray-level image to compensate for distortion. These results also showed the validity of the process and the applicability of the analytical method. >

Three-dimensional location estimation of circular features for machine vision

Current approaches towards achieving mobility in the workplace are reviewed. The role of automatic guided vehicles (AGVs) and some of the preliminary work of other groups in autonomous vehicles are described. An overview is presented of the autonomous robot architecture (AuRA), a general-purpose system designed for experimentation in the domain of intelligent mobility. The means by which navigation is accomplished within this framework is specifically addressed. A description is given of the changes made to AuRA to adapt it to a flexible manufacturing environment, the types of knowledge that need to be incorporated, and the new motor behaviors required for this domain. Simulations of both navigational planning and reactive/reflexive motor schema-based navigation in a flexible manufacturing systems environment, followed by actual navigational experiments using the mobile vehicle, are presented. >

Autonomous navigation in a manufacturing environment

As mobile robots are taking on more and more of the tasks that were normally delegated to humans, they need to acquire higher degrees of autonomous operation, which calls for accurate and efficient position determination and/or verification The critical geometric dimensions of a standard pattern are used here to locate the relative position of the mobile robot with respect to the pattern; by doing so, the method does not depend on values of any intrinsic camera parameters, except the focal length In addition, this method has the advantages of simplicity and flexibility This standard pattern is also provided with a unique identification code, using bar codes, that enables the system to find the absolute location of the pattern These bar codes also assist in the scanning algorithms to locate the pattern in the environment A thorough error analysis and experimental results obtained through software simulation are presented, as well as the current direction of our work

Position verification of a mobile robot using standard pattern

A computer vision method is presented to determine the 3-D spatial locations of joints or feature points of human body from a film recording the human motion during walking. The proposed method first applies the geometric projection theory to obtain a set of feasible postures from a single image, then it makes use of the given dimensions of the human stick figure, physiological and motion-specific knowledge to constrain the feasible postures in both the single-frame analysis and the multi-frame analysis. Finally a unique gait interpretation is selected by an optimization algorithm. Computer simulations are used to illustrate the ideas presented. >

/pdf/knowledge-guided-visual-perception-of-3-d-human-gait-from-a-3ybq89bh0i.pdf

Knowledge-guided visual perception of 3-D human gait from a single image sequence

TV image processing to determine the position of a robot vehicle

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TV image processing to determine the position of a robot vehicle