Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/26242
Title: Agent based path planning for Robot navigation
Researcher: Tamilselvi D
Guide(s): Mercy shalinie S
Keywords: Distance Transform Agent
Dynamic Path Planning Agent
Genetic Algorithm
Gilbert Johnson Keerthi
Information and Communication engineering
Reinforcement Learning
Upload Date: 30-Sep-2014
University: Anna University
Completed Date: 01-12-2012
Abstract: The objective of this research is to develop an Agent Based newlineFramework for planning the path of a robot during its mobility both in static newlineand dynamic environment Robot Path planning algorithms such as Distance newlineTransform Agent DTA Dynamic Path Planning Agent DPPA newlineReinforcement Learning RL Genetic Algorithm GA and Hybrid approach newlineof Genetic Algorithm with Gilbert Johnson Keerthi GJK will enable the newlineagents to make shortest optimal path selection with various obstacles in an newlineindoor environment effectively newlineThe Distance Transform Agent provides subtask to each agent for newlineeffective navigation The path planning agent and obstacles agent share the newlinedistance as common criteria and selects the path for mobile robot navigation newlineThe distance calculation done by the Distance Transform Agent predicts the newlineposition of the static obstacle in advance and makes the robot find the shortest newlinepath Non existence of path was predicted in prior and informed to the robot newlinebefore navigation newline newline
Pagination: xvii, 173p.
URI: http://hdl.handle.net/10603/26242
Appears in Departments:Faculty of Information and Communication Engineering

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04_acknowledgement.pdf6.73 kBAdobe PDFView/Open
05_content.pdf23.44 kBAdobe PDFView/Open
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07_chapter2.pdf871.05 kBAdobe PDFView/Open
08_chapter3.pdf666.97 kBAdobe PDFView/Open
09_chapter4.pdf906.36 kBAdobe PDFView/Open
10_chapter5.pdf583.86 kBAdobe PDFView/Open
11_chapter6.pdf499.63 kBAdobe PDFView/Open
12_chapter7.pdf10.67 kBAdobe PDFView/Open
13_reference.pdf63.9 kBAdobe PDFView/Open
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