TY - GEN
T1 - Development of a Light Weight Autonomous Lawn Mower and Performance Analysis using Fuzzy Logic Technique
AU - Okwu, Modestus O.
AU - Tartibu, Lagouge K.
AU - Enarevba, Dolor Roy
AU - Oyejide, Oluwayomi J.
AU - Otanocha, Omonigho B.
AU - Adumene, Sidum
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - autonomous lawn mower
KW - path planning
KW - performance analysis
UR - http://www.scopus.com/inward/record.url?scp=85137988364&partnerID=8YFLogxK
U2 - 10.1109/icABCD54961.2022.9856342
DO - 10.1109/icABCD54961.2022.9856342
M3 - Conference contribution
AN - SCOPUS:85137988364
T3 - 5th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2022 - Proceedings
BT - 5th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2022 - Proceedings
A2 - Pudaruth, Sameerchand
A2 - Singh, Upasana
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2022
Y2 - 4 August 2022 through 5 August 2022
ER -