Paper
21 March 1989 Autonomous Knowledge-Based Navigation In An Unkown Two-Dimensional Environment With Convex Polygon Obstacles
Linfu Cheng, John D. McKendrick
Author Affiliations +
Abstract
Navigation of autonomous vehicles in environments where the exact locations of obstacles are know has been the focus of research for two decades. More recently, algorithms for controlling progress through unknown environments have been proposed. The utilization of knowledge-based systems for studying the behavior of an autonomous vehicles has not received much study. A knowledge-driven autonomous system simulation was developed which enabled an autonomous mobile system to move in a two-dimensional environment and to use a simulated ranging/vision sensor to test whether a selected goal position was visible or whether the goal was obscured by one of the multiple polygon obstacles. As the mobile system gains information about the location of obstacles, it is added to the system's knowledge-base. Considerable attention was given to the computation of what vertices were mutually visible in the multi-obstacle environment and that computation was carried out in Lisp. The study relied on a program implemented in a generalized decision-making paradigm, OPS5.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Linfu Cheng and John D. McKendrick "Autonomous Knowledge-Based Navigation In An Unkown Two-Dimensional Environment With Convex Polygon Obstacles", Proc. SPIE 1095, Applications of Artificial Intelligence VII, (21 March 1989); https://doi.org/10.1117/12.969323
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KEYWORDS
Visibility

Sensors

Navigation systems

Artificial intelligence

Computer simulations

Environmental sensing

Computing systems

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