Development of a Light Weight Autonomous Lawn Mower and Performance Analysis using Fuzzy Logic Technique

Modestus O. Okwu, Lagouge K. Tartibu, Dolor Roy Enarevba, Oluwayomi J. Oyejide, Omonigho B. Otanocha, Sidum Adumene

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This study is focused on the development of a lightweight autonomous lawn mower with obstacle avoidance mechanism. A suitable architecture has been defined for the modular lawn mower, which consist of a 12V direct current (DC) geared motor, Driver IC, IR infrared obstacle avoidance sensor, ultrasonic sensors for monitoring grass level, S Light lithium batteries, PSI sensor for obstacle avoidance, cutting blade made from aluminum plate, tire, Arduino Micro controller, Vero board, Electronic components, Fasteners. As humans, seek to And a more efficient, less stressful, and low maintenance means of doing work, especially keeping a tidy lawn for a cleaner and greener environment, several means have been implored from the use of sharpened metal faces to the use of locally fabricated and fuel powered lawn mower. These traditional methods of clearing the lawn through manual and mechanically driven mechanisms are laborious, a reliable autonomous system is required to provide higher accuracy in cutting operation This research makes contribution in that direction, it is focused on developing a lawn mower capable of trimming grass on the lawn timely and autonomously. The design and fabrication of the ALM was achieved by using locally sought materials. Typically, an ALM requires the setup of a boundary wire to locate the working environment and use of different sensors for effective functionality. Sensors such as ultrasonic sensors, PSI sensors, are implored into the development of the system, to facilitate proper function of the robot. The developed ALM is obstacle sensitive and have the ability to function in the domestic lawn autonomously. The total intelligent system (TIS) of the developed system was tested using Fuzzy Logic technique and it showed good cutting efficiency of 62% and satisfactory obstacle avoidance during cutting operation at reduced labour cost. A modified version can be developed for use in schools, homes, office environment and football stadium for excellent cutting operation.

Original languageEnglish
Title of host publication5th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2022 - Proceedings
EditorsSameerchand Pudaruth, Upasana Singh
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665484220
DOIs
Publication statusPublished - 2022
Event5th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2022 - Durban, South Africa
Duration: 4 Aug 20225 Aug 2022

Publication series

Name5th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2022 - Proceedings

Conference

Conference5th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2022
Country/TerritorySouth Africa
CityDurban
Period4/08/225/08/22

Keywords

  • autonomous lawn mower
  • path planning
  • performance analysis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Information Systems and Management
  • Education

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