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Towards an artificial neural network-based simulator for behavioural evolution in evolutionary robotics

Published: 12 October 2009 Publication History

Abstract

It is not apparent to employ an Artificial Neural Network (ANN) as simulator structure during the Evolutionary Robotics (ER) process. Consequently, the potential for the use of an ANN in this regard has been investigated in this paper. This simulator Neural Network (NN) was trained to predict changes in the position and orientation resulting from arbitrary motor commands sent to a Lego Mindstorms NXT robot moving in a two-dimensional plane. The proposed NN simulator was employed as an alternative to conventional physics-engine based simulators to evolve simple navigation behaviour in said robot and encouraging results were obtained.

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  • (2019)Towards the Incorporation of Proprioception in Evolutionary Robotics Controllers2019 Third IEEE International Conference on Robotic Computing (IRC)10.1109/IRC.2019.00041(226-229)Online publication date: Feb-2019
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cover image ACM Other conferences
SAICSIT '09: Proceedings of the 2009 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists
October 2009
225 pages
ISBN:9781605586434
DOI:10.1145/1632149
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 12 October 2009

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Author Tags

  1. Lego mindstorms
  2. evolutionary robotics
  3. simulator neural networks

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SAICSIT '09

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Cited By

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  • (2021)Adaptive Navigation Strategies in Evolutionary Robotics Controllers with Location Perception2021 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC45853.2021.9504759(2499-2506)Online publication date: 28-Jun-2021
  • (2020)An Evaluation of a Bootstrapped Neuro-Evolution ApproachConference of the South African Institute of Computer Scientists and Information Technologists 202010.1145/3410886.3410896(156-167)Online publication date: 14-Sep-2020
  • (2019)Towards the Incorporation of Proprioception in Evolutionary Robotics Controllers2019 Third IEEE International Conference on Robotic Computing (IRC)10.1109/IRC.2019.00041(226-229)Online publication date: Feb-2019
  • (2018)Robotic snake simulation using ensembles of artificial neural networks in evolutionary roboticsProceedings of the Genetic and Evolutionary Computation Conference10.1145/3205455.3205507(173-180)Online publication date: 2-Jul-2018
  • (2018)Neural Networks for Mobile Robot Inverse Kinematics2018 Eighth International Conference on Information Science and Technology (ICIST)10.1109/ICIST.2018.8426142(237-244)Online publication date: Jun-2018
  • (2017)Concurrent controller and Simulator Neural Network development for a snake-like robot in Evolutionary RoboticsRobotics and Autonomous Systems10.1016/j.robot.2016.11.01888:C(37-50)Online publication date: 1-Feb-2017
  • (2017)Neuroevolution of Inverted Pendulum ControlJournal of Intelligent and Robotic Systems10.1007/s10846-017-0465-186:3-4(419-445)Online publication date: 1-Jun-2017
  • (2016)Concurrent controller and Simulator Neural Network development for a differentially-steered robot in Evolutionary RoboticsRobotics and Autonomous Systems10.1016/j.robot.2015.10.01176:C(80-92)Online publication date: 1-Feb-2016
  • (2015)Evolving Snake Robot Controllers Using Artificial Neural Networks as an Alternative to a Physics-Based Simulator2015 IEEE Symposium Series on Computational Intelligence10.1109/SSCI.2015.47(267-274)Online publication date: Dec-2015
  • (2012)Simulating Robots Without Conventional Physics: A Neural Network ApproachJournal of Intelligent & Robotic Systems10.1007/s10846-012-9782-671:3-4(319-348)Online publication date: 13-Oct-2012
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