Position Estimation of In-Pipe Robot using Artificial Neural Network and Sensor Fusion
| Autor: | Ömür Aydoğmuş, Muhammed Fatih Talu, Abdullah Erhan Akkaya |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Artificial neural network
Computer science Position (vector) business.industry Computer Science Interdisciplinary Application General Engineering Robot Computer vision Artificial intelligence Sensor fusion business Sensor Fusion Artificial Neural Network Inertial Navigation Leak Detection Bilgisayar Bilimleri Disiplinler Arası Uygulamalar |
| Zdroj: | Volume: 25, Issue: 5 1102-1120 Sakarya University Journal of Science |
| ISSN: | 2147-835X |
| Popis: | Water is vital for all living beings, especially for a human. Automatic position detection of water leakage in water pipelines is very important to minimize the loss of labour, time, money spent on exploration and excavation in pipe inspection procedures. The main goal of detection is to prevent water loss. In this study, sensitive position detection, crack frequency band detection and external sphere studies of an in-pipe robot prototype have performed. During the precise position estimation, classical EKF, stationary region detection and location estimation using EHDE are performed with two different ANNs. In this way, online precise position estimation can be done on hardware that has not sufficient computational power for indoor robotic studies. In addition, the sound characteristics resulting from the crack at different hole size and water pressure intensity levels have investigated. Finally, a new sealing sphere design has devised and three different hydrophone sensor data have recorded on the SD card simultaneously. It has been found that the proposed ANN method has the performance to work online and can make a similar position estimation with the classical IMU position estimation method by 99%. |
| Databáze: | OpenAIRE |
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