Research Article
An Algorithmic Approach to Adapting Edge-based Devices for Autonomous Robotic Navigation
@ARTICLE{10.4108/eai.5-8-2021.170559, author={Mbadiwe S. Benyeogor and Kosisochukwu P. Nnoli and Oladayo O. Olakanmi and Olusegun I. Lawal and Eric J. Gratton and Sushant Kumar and Kenneth A. Akpado and Piyal Saha}, title={An Algorithmic Approach to Adapting Edge-based Devices for Autonomous Robotic Navigation}, journal={EAI Endorsed Transactions on Context-aware Systems and Applications}, volume={8}, number={1}, publisher={EAI}, journal_a={CASA}, year={2021}, month={8}, keywords={autonomous navigation, edge computing, intelligence schema, localization, obstacle avoidance}, doi={10.4108/eai.5-8-2021.170559} }- Mbadiwe S. Benyeogor
Kosisochukwu P. Nnoli
Oladayo O. Olakanmi
Olusegun I. Lawal
Eric J. Gratton
Sushant Kumar
Kenneth A. Akpado
Piyal Saha
Year: 2021
An Algorithmic Approach to Adapting Edge-based Devices for Autonomous Robotic Navigation
CASA
EAI
DOI: 10.4108/eai.5-8-2021.170559
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.
Copyright © 2021 M. S. Benyeogor et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
