An Algorithmic Approach to Adapting Edge-based Devices for Autonomous Robotic Navigation

Authors

  • Mbadiwe S. Benyeogor Automata Research Group (ARG), OEMA Tools and Automation Ltd., Ibadan, Nigeria
  • Kosisochukwu P. Nnoli Jacobs University image/svg+xml
  • Oladayo O. Olakanmi Automata Research Group (ARG), OEMA Tools and Automation Ltd., Ibadan, Nigeria
  • Olusegun I. Lawal National Space Research and Development Agency image/svg+xml
  • Eric J. Gratton Automata Research Group (ARG), OEMA Tools and Automation Ltd., Ibadan, Nigeria
  • Sushant Kumar Automata Research Group (ARG), OEMA Tools and Automation Ltd., Ibadan, Nigeria
  • Kenneth A. Akpado Nnamdi Azikiwe University image/svg+xml
  • Piyal Saha Automata Research Group (ARG), OEMA Tools and Automation Ltd., Ibadan, Nigeria

DOI:

https://doi.org/10.4108/eai.5-8-2021.170559

Keywords:

autonomous navigation, edge computing, intelligence schema, localization, obstacle avoidance

Abstract

A recent significant progress has been made in development of intelligent mobile robots that is capable of autonomous navigation using an edge-computing system. This could sense changes in its environment to control its mechanical behavior towards accomplishing preprogrammed motions. Several algorithms were used in developing the robot’s control software. These include the moving average filter, the extended Kalman filter, and the covariance algorithm. Using these algorithms, the robot could learn from its sensors to estimate and control its position, velocity, and the proximity of obstacles along its path, while autonomously navigating to a predetermined location on the earth’s surface. Results show that our algorithmic approach to developing software systems for autonomous robots using edge-computing devices is viable, cost-efficient, and robust. Hence, our work is a proof of concept for the further development of edge-based intelligence and autonomous robots.

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Published

21-06-2022

How to Cite

1.
Benyeogor MS, Nnoli KP, Olakanmi OO, Lawal OI, Gratton EJ, Kumar S, Akpado KA, Saha P. An Algorithmic Approach to Adapting Edge-based Devices for Autonomous Robotic Navigation. EAI Endorsed Trans Context Aware Syst App [Internet]. 2022 Jun. 21 [cited 2022 Oct. 1];8(1):e2. Available from: https://publications.eai.eu/index.php/casa/article/view/1535