Akademik Veri Yönetim Sistemi
Multimedia Tools and Applications, 2024 (SCI-Expanded)
This study provides insights into a smart and autonomous robotic design with a Node-RED as a low code and Internet of Things architecture, advancing the wall-climbing robot design and construction field. The robot makes use of a special palletized mechanism that adheres magnetically. This includes an anti-slip design and powerful magnetic forces that enable the robot to be attached to the wall. It is overcoming locomotion challenges such as magnetic adhesion, slippery issues, gravity forces, and Coulomb friction. The work focuses on manufacturing a robot equipped with essential hardware and software, actuators, and sensors, enabling reliable control algorithms for locomotion and inspection. The robot can interact in resource-intensive and hazardous environments thanks to the Internet of Things, which also enhances the system's visualization and monitoring functions. A visual corrosion diagnostic display and deep learning-based corrosion inspection algorithms training and testing enhance visual inspection. This work validates a control strategy against high gravitational, magnetic, and Coulomb friction forces. A robot based on differential driving with direct current motors is built. Its features include autonomous trajectory tracking on vertical surfaces in the presence of high disturbances and the capacity to produce references and adjust positioning utilizing a fusion of sensors and a Kalman filter to enhance autonomous driving while minimizing noise. This study provides insights into a smart and autonomous robotic design with a Node-RED as a low code and Internet of Things architecture, advancing the wall-climbing robot design and construction field. The robot makes use of a special palletized mechanism that adheres magnetically. This includes an anti-slip design and powerful magnetic forces that enable the robot to be attached to the wall. It is overcoming locomotion challenges such as magnetic adhesion, slippery issues, gravity forces, and Coulomb friction. The work focuses on manufacturing a robot equipped with essential hardware and software, actuators, and sensors, enabling reliable control algorithms for locomotion and inspection. The robot can interact in resource-intensive and hazardous environments thanks to the Internet of Things, which also enhances the system's visualization and monitoring functions. A visual corrosion diagnostic display and deep learning-based corrosion inspection algorithms training and testing enhance visual inspection. This work validates a control strategy against high gravitational, magnetic, and Coulomb friction forces. A robot based on differential driving with direct current motors is built. Its features include autonomous trajectory tracking on vertical surfaces in the presence of high disturbances and the capacity to produce references and adjust positioning utilizing a fusion of sensors and a Kalman filter to enhance autonomous driving while minimizing noise.