Abstract
Detection and localization of escaped hazardous gases is of great industrial and public interest in order to prevent harm to humans, nature and assets or just to prevent financial losses. The development of novel leak-detection technologies will yield better coverage of inspected objects while helping to lower plant operation costs at the same time. Moreover, inspection personnel can be relieved from repetitive work and focus on value-adding supervisory control and optimization tasks. The proposed system consists of autonomous mobile inspection robots that are equipped with several remote gas sensing devices and local intelligence. All-terrain robots with caterpillar tracks are used that can handle slopes, unpaved routes and offer maneuverability in restricted spaces as required for inspecting plants such as petroleum refineries, tank farms or chemical sites as well as sealed landfills. The robots can detect and locate gas leaks autonomously to a great extent using infrared optical spectroscopic and thermal remote sensing techniques and data processing. This article gives an overview of the components of the robotic system prototype, i.e. the robotic platform and the remote sensing and evaluation module. The software architecture, including the robot middleware and the measurement routines, are described. Results from testing autonomous mobility and object inspection functions in a large test course are presented.
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Notes
- 1.
See www.robogasinspector.de for further information.
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Acknowledgments
The project \(\text {RoboGas}^{Inspector}\) is funded by the Federal Ministry of Economics and Technology due to a resolution of the German Bundestag. The authors would like to thank the other project partners for their valuable discussions and support as well as Dr.-Ing. R. Hassinger and Dipl-Ing. R. Feldner for very obligingly providing the test hall.
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Soldan, S., Welle, ., Barz, T., Kroll, A., Schulz, D. (2014). Towards Autonomous Robotic Systems for Remote Gas Leak Detection and Localization in Industrial Environments. In: Yoshida, K., Tadokoro, S. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 92. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40686-7_16
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