Field-programmable gate arrays
Field-programmable gate arrays
Circuit synthesis with VHDL
VHDL for programmable logic
Connecting the Physical World with Pervasive Networks
IEEE Pervasive Computing
SLAVE: a genetic learning system based on an iterative approach
IEEE Transactions on Fuzzy Systems
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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.