A genetic_FPGA algorithm path planning of an autonomous mobile robot
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Date
2010
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Abstract
This paper proposes Genetic Algorithms (GAs) for path Autonomous Mobile Robot (AMR). This approach has an advantage of adaptivity such that the GA works perfectly even if an environment is unknown. First, we present a software implementation GA path planning in a terrain. The results gotten of the GA on randomly generated terrains are very satisfactory and promising . Second, we discuss extensions of the GA for solving both paths planning and trajectory planning using a Single Static Random Access Memory (SRAM) for Field Programmable Gate Array (FPGA). This new design methodology based upon a VHDL description of the path planning has the two (02) advantages : to present a real autonomous task for mobile robots, and being generic and flexible and can be changed at the user demand. The results gotten are promising
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Keywords
Genetic Algorithm (GA), Autonomous Mobile Robot (AMR), FPGA implementation, VHDL, Synthesis, Galileo
