Knowledge-based control for robot self-localization

Autonomous robot systems are being proposed for a variety of missions including the Mars rover/sample return mission. Prior to any other mission objectives being met, an autonomous robot must be able to determine its own location. This will be especially challenging because location sensors like GPS, which are available on Earth, will not be useful, nor will INS sensors because their drift is too large. Another approach to self-localization is required. In this paper, we describe a novel approach to localization by applying a problem solving methodology. The term 'problem solving' implies a computational technique based on logical representational and control steps. In this research, these steps are derived from observing experts solving localization problems. The objective is not specifically to simulate human expertise but rather to apply its techniques where appropriate for computational systems. In doing this, we describe a model for solving the problem and a system built on that model, called localization control and logic expert (LOCALE), which is a demonstration of concept for the approach and the model. The results of this work represent the first successful solution to high-level control aspects of the localization problem

Deictic primitives for general purpose navigation

A visually-based deictic primative used as an elementary command set for general purpose navigation was investigated. It was shown that a simple 'follow your eyes' scenario is sufficient for tracking a moving target. Limitations of velocity, acceleration, and modeling of the response of the mechanical systems were enforced. Realistic paths of the robots were produced during the simulation. Scientists could remotely command a planetary rover to go to a particular rock formation that may be interesting. Similarly an expert at plant maintenance could obtain diagnostic information remotely by using deictic primitives on a mobile are used in the deictic primitives, we could imagine that the exact same control software could be used for all of these applications

Indoor mobile robot navigation with continuous localization.

by Lam Chin Hung.Thesis (M.Phil.)--Chinese University of Hong Kong, 1999.Includes bibliographical references (leaves 60-64).Abstracts in English and Chinese.Acknowledgments --- p.iiList of Figures --- p.vList of Tables --- p.viiAbstract --- p.viiiChapter 1 --- Introduction --- p.1Chapter 2 --- Algorithm Outline --- p.7Chapter 2.1 --- Assumptions --- p.7Chapter 2.2 --- Robot Localization --- p.8Chapter 2.3 --- Algorithm Outline --- p.11Chapter 3 --- Global and Local Maps --- p.15Chapter 3.1 --- Feature Selection --- p.17Chapter 3.2 --- Line Correspondence --- p.18Chapter 3.3 --- Map Representation --- p.20Chapter 3.3.1 --- Global Map --- p.21Chapter 3.3.2 --- Local Map --- p.22Chapter 3.4 --- Integration of Multiple Local 2D Maps --- p.24Chapter 4 --- Localization Algorithm --- p.27Chapter 4.1 --- Robot Orientation --- p.28Chapter 4.2 --- Robot Position --- p.29Chapter 4.2.1 --- Match Function --- p.30Chapter 4.2.2 --- Search Algorithm --- p.31Chapter 4.3 --- Continuous Localization with Retroactive Pose Update --- p.32Chapter 5. --- Implementation and Experiments --- p.35Chapter 5.1 --- Computing Robot Orientation --- p.36Chapter 5.2 --- Robot Position by Map Registration --- p.42Chapter 5.2.1 --- Error Analysis --- p.47Chapter 5.3 --- Discussions --- p.49Chapter 6. --- Conclusion --- p.52Appendix --- p.54Chapter A.l --- Intrinsic and Extrinsic Parameters --- p.54Chapter A.2 --- Relation Between Cameras (Stereo Camera Calibration) --- p.55Chapter A.3 --- Wheel-Eyes Calibration --- p.56Chapter A.4 --- Epipolar Geometry --- p.58Chapter A.5 --- The Tele-operate Interface --- p.59References --- p.6

An Incremental Navigation Localization Methodology for Application to Semi-Autonomous Mobile Robotic Platforms to Assist Individuals Having Severe Motor Disabilities.

In the present work, the author explores the issues surrounding the design and development of an intelligent wheelchair platform incorporating the semi-autonomous system paradigm, to meet the needs of individuals with severe motor disabilities. The author presents a discussion of the problems of navigation that must be solved before any system of this type can be instantiated, and enumerates the general design issues that must be addressed by the designers of systems of this type. This discussion includes reviews of various methodologies that have been proposed as solutions to the problems considered. Next, the author introduces a new navigation method, called Incremental Signature Recognition (ISR), for use by semi-autonomous systems in structured environments. This method is based on the recognition, recording, and tracking of environmental discontinuities: sensor reported anomalies in measured environmental parameters. The author then proposes a robust, redundant, dynamic, self-diagnosing sensing methodology for detecting and compensating for hidden failures of single sensors and sensor idiosyncrasies. This technique is optimized for the detection of spatial discontinuity anomalies. Finally, the author gives details of an effort to realize a prototype ISR based system, along with insights into the various implementation choices made

The 1993 Goddard Conference on Space Applications of Artificial Intelligence

This publication comprises the papers presented at the 1993 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, MD on May 10-13, 1993. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed