A Comparison of a Digital and Floating-Point Virtual Programmable Logic Device and an Artifical Neural Network Evolved for Robotic Navigation

Created by W.Langdon from gp-bibliography.bib Revision:1.7975

@InProceedings{borrett:2024:CEC2,

• author = "Fraser Borrett and Mark Beckerleg",
• title = "A Comparison of a Digital and Floating-Point Virtual Programmable Logic Device and an Artifical Neural Network Evolved for Robotic Navigation",
• booktitle = "2024 IEEE Congress on Evolutionary Computation (CEC)",
• year = "2024",
• editor = "Bing Xue",
• address = "Yokohama, Japan",
• month = "30 " # jun # " - 5 " # jul,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, Program processors, Navigation, Programmable logic devices, Artificial neural networks, Evolutionary computation, Software, Hardware, Virtual Programmable Logic Device, Evolvable Hardware, Artificial Neural Network, Robotic Navigation, Genetic Algorithm",
• isbn13 = "979-8-3503-0837-2",
• DOI = "doi:10.1109/CEC60901.2024.10612180",
• abstract = "Two novel architectures, the digital and floatingpoint virtual programmable logic device (VPLD) are compared with an artificial neural network, evolved for the robotic navigational tasks of obstacle avoidance and light following for a two wheeled robot. The VPLD is based on a programmable logic device but is coded in software rather than in hardware. This allows the VPLD to be implemented on CPUs allowing it to be run on a wide range of platforms including PCs, mobile phones and ARM processors. The function of the VPLD is governed by a configuration bitstream which can be evolved by evolutionary computation. It was found that the digital and floating-point VPLDs performed well against the ANN in the navigational tasks, making the VPLD a viable alternative to an ANN for robotic navigation.",
• notes = "also known as \cite{10612180}

  WCCI 2024",

}

Genetic Programming entries for Fraser Borrett Mark Beckerleg

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