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Lookup NU author(s): Dr John Hedley
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
This paper describes the development of a convolutional neural network for the control of a home monitoring robot (FumeBot). The robot is fitted with a Raspberry Pi for on board control and a Raspberry Pi camera is used as the data feed for the neural network. A wireless connection between the robot and a graphical user interface running on a laptop allows for the diagnostics and development of the neural network. The neural network, running on the laptop, was trained using a supervised training method. The robot was put through a series of obstacle courses to test its robustness, with the tests demonstrating that the controller has learned to navigate the obstacles to a reasonable level. The main problem identified in this work was that the neural controller did not have memory of past actions it took and a past state of the world resulting in obstacle collisions. Options to rectify this issue are suggested.
Author(s): Thomas A, Hedley J
Publication type: Article
Publication status: Published
Online publication date: 29/07/2019
Acceptance date: 25/07/2019
Date deposited: 21/08/2019
ISSN (electronic): 2218-6581
Publisher: M D P I AG
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