TY - GEN
T1 - Development of a Modular Wall Painting Robot for Hazardous Environment
AU - Okwu, Modestus
AU - Tartibu, Lagouge
AU - Otanocha, Omonigho B.
AU - Enarevba, Dolor R.
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/5
Y1 - 2021/8/5
N2 - This research output demonstrates a modular wall painting robot (WPR) with inbuilt remote control, for application in hazardous environments. The mechanical system was designed and fabricated using locally sourced material. The specific materials for the setup include steel for the frame of the robot, wooden material for the arm, waste water dispenser bottle for paint reservoir, 12V DC motors, 24V DC electric motor, surface pump (0.5hp), hose, tires, roller, micro-controller unit, wires, and bottom frame. The roller is fed by a pump that lifts the paint at stipulated intervals while it performs the up and down reciprocating motion during robotic arm operations. The setup was automated and synchronized by means of a microcontroller programmable unit. The performance of the robot was rated high using classical metric system. The limitation of this research is in the aspect of repeatability and precision during painting process, due to the dexterity of the arm. Further studies can be conducted on the control of the arm. The novelty of this research include the re-use of: waste plastic water dispenser bottle as paint reservoir; light wooden material for upper and lower arm of the robot; DC motor from an abandoned Benz car as programmable stepper and waste tubeless tires from defunct trolleys as tyres for the WPR. The developed system can be scaled up to support painting in the oil and gas equipment and infrastructures in confined space settings. It will significantly reduce labour costs; eliminate possible threats posed to human health; reduce the total time taken to accomplish the task; enhance reliability, productivity, and surface finishes. This research output is original, sustainable and environmentally friendly. It has demonstrated the possibility of converting waste material into useful robots in the era of Industry 4.0.
AB - This research output demonstrates a modular wall painting robot (WPR) with inbuilt remote control, for application in hazardous environments. The mechanical system was designed and fabricated using locally sourced material. The specific materials for the setup include steel for the frame of the robot, wooden material for the arm, waste water dispenser bottle for paint reservoir, 12V DC motors, 24V DC electric motor, surface pump (0.5hp), hose, tires, roller, micro-controller unit, wires, and bottom frame. The roller is fed by a pump that lifts the paint at stipulated intervals while it performs the up and down reciprocating motion during robotic arm operations. The setup was automated and synchronized by means of a microcontroller programmable unit. The performance of the robot was rated high using classical metric system. The limitation of this research is in the aspect of repeatability and precision during painting process, due to the dexterity of the arm. Further studies can be conducted on the control of the arm. The novelty of this research include the re-use of: waste plastic water dispenser bottle as paint reservoir; light wooden material for upper and lower arm of the robot; DC motor from an abandoned Benz car as programmable stepper and waste tubeless tires from defunct trolleys as tyres for the WPR. The developed system can be scaled up to support painting in the oil and gas equipment and infrastructures in confined space settings. It will significantly reduce labour costs; eliminate possible threats posed to human health; reduce the total time taken to accomplish the task; enhance reliability, productivity, and surface finishes. This research output is original, sustainable and environmentally friendly. It has demonstrated the possibility of converting waste material into useful robots in the era of Industry 4.0.
KW - autonomous system
KW - confined space
KW - hazard
KW - wall painting robot
UR - http://www.scopus.com/inward/record.url?scp=85115379466&partnerID=8YFLogxK
U2 - 10.1109/icABCD51485.2021.9519330
DO - 10.1109/icABCD51485.2021.9519330
M3 - Conference contribution
AN - SCOPUS:85115379466
T3 - icABCD 2021 - 4th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, Proceedings
BT - icABCD 2021 - 4th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, Proceedings
A2 - Pudaruth, Sameerchand
A2 - Singh, Upasana
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2021
Y2 - 5 August 2021 through 6 August 2021
ER -