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Title: Path planning and obstacle avoidance hybrid system using a connectionist network. (Final report). Master's thesis

Abstract

Automated path planning and obstacle avoidance has been the subject of intensive research in recent times. Most efforts in the field of semiautonomous mobile-robotic navigation involve using Artificial Intelligence search algorithms on a structured environment to achieve either good or optimal paths. Other approaches, such as incorporating Artificial Neural Networks, have also been explored. By implementing a hybrid system using the parallel-processing features of connectionist networks and simple localized search techniques, good paths can be generated using only low-level environmental sensory data. This system can negotiate structured two- and three-dimensional grid environments, from a start position to a goal, while avoiding all obstacles. Major advantages of this method are that solution paths are good in a global sense and path planning can be accomplished in real time if the system is implemented in customized parallel-processing hardware. This system has been proven effective in solving two- and three-dimensional maze-type environments.

Authors:
Publication Date:
Research Org.:
Rice Univ., Houston, TX (USA)
OSTI Identifier:
6472571
Report Number(s):
AD-A-223806/1/XAB
Resource Type:
Technical Report
Resource Relation:
Other Information: Thesis
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; ROBOTS; OPTIMIZATION; ALGORITHMS; ARRAY PROCESSORS; ARTIFICIAL INTELLIGENCE; AUTOMATION; HYBRID COMPUTERS; NAVIGATION; NEURAL NETWORKS; PARALLEL PROCESSING; PLANNING; POSITION SENSITIVE DETECTORS; PROGRESS REPORT; REAL TIME SYSTEMS; THREE-DIMENSIONAL CALCULATIONS; COMPUTERS; DOCUMENT TYPES; MATHEMATICAL LOGIC; MEASURING INSTRUMENTS; PROGRAMMING; RADIATION DETECTORS; 990200* - Mathematics & Computers; 990300 - Information Handling

Citation Formats

Schuster, C E. Path planning and obstacle avoidance hybrid system using a connectionist network. (Final report). Master's thesis. United States: N. p., 1990. Web.
Schuster, C E. Path planning and obstacle avoidance hybrid system using a connectionist network. (Final report). Master's thesis. United States.
Schuster, C E. 1990. "Path planning and obstacle avoidance hybrid system using a connectionist network. (Final report). Master's thesis". United States.
@article{osti_6472571,
title = {Path planning and obstacle avoidance hybrid system using a connectionist network. (Final report). Master's thesis},
author = {Schuster, C E},
abstractNote = {Automated path planning and obstacle avoidance has been the subject of intensive research in recent times. Most efforts in the field of semiautonomous mobile-robotic navigation involve using Artificial Intelligence search algorithms on a structured environment to achieve either good or optimal paths. Other approaches, such as incorporating Artificial Neural Networks, have also been explored. By implementing a hybrid system using the parallel-processing features of connectionist networks and simple localized search techniques, good paths can be generated using only low-level environmental sensory data. This system can negotiate structured two- and three-dimensional grid environments, from a start position to a goal, while avoiding all obstacles. Major advantages of this method are that solution paths are good in a global sense and path planning can be accomplished in real time if the system is implemented in customized parallel-processing hardware. This system has been proven effective in solving two- and three-dimensional maze-type environments.},
doi = {},
url = {https://www.osti.gov/biblio/6472571}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Jun 01 00:00:00 EDT 1990},
month = {Fri Jun 01 00:00:00 EDT 1990}
}

Technical Report:
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