Limpet: a multi-sensing robotic platform for monitoring offshore energy platforms

Abstract

Abstract: The oil and gas industry faces increasing pressure to remove people from dangerous offshore environments for health and safety reasons, and to look for more cost-effective and safer methods for inspection, repair and maintenance of their offshore energy platforms. Robots are seen as key enablers in this regard, as they present a safer, cheaper, and more efficient way to inspect and monitor offshore infrastructure. In this thesis, I develop a new multi-sensing robotic platform, the Limpet, which is designed to be lowcost and highly manufacturable, and thus can be deployed in large collectives for monitoring offshore energy platforms. The Limpet is developed as part of the flagship ORCA (Offshore Robotics for Certification of Assets) Hub in the United Kingdom. The Limpet is designed to be one part of a heterogeneous collection of field robots (drones, UAVs, mobile legged robots etc.) that together with the offshore assets comprise the ORCA Hub System for asset certification and management. The Limpet comprises the sensing aspect of the ORCA Hub System, where sensing is a key element in asset monitoring, fault detection, mapping, environmental monitoring and helping other robots navigate around the platform. The Limpet has nine different sensing modalities, which are: temperature; pressure; humidity; optical; distance; sound; magnetic field; accelerometer; gyroscope. I have integrated the Limpet with Robot Operating System (ROS) to allow it to communicate with other robots within the ORCA Hub System, where the interaction between the different robots results in more complex and useful behavior. The Limpet was designed to have robust communication, where it can use one of multiple communication systems for data transmission or communication with other agents. In this thesis, I demonstrate how the Limpet could be used for real-time condition monitoring of offshore structures, by combining remote sensing with signal processing techniques. I show an example of the condition monitoring approach by using the system to monitor the condition of a wind turbine. I also show how the processing and analysis of the data from the sensors in the condition monitoring approach can be done on-board using the microcontroller, which can improve the communication requirements of the system. In this thesis, I also show a few examples of how the Limpet can be deployed in offshore environments using other robotic systems. To allow the Limpet to navigate the unstructured offshore environment efficiently after deployment and increase its accessible areas to be useful for monitoring and inspection tasks, I have developed an adhesion and locomotion mechanism for the Limpet based on electromagnetic modules (EMMs). These capabilities allows it to adhere to and climb surfaces at different angles, which makes it a more useful tool for monitoring offshore environments. The adhesion and locomotion systems are designed in a modular fashion, as modular systems can be easily reconfigured, giving the robot more robustness and capability for achieving new tasks. Finally, due to the lack of accuracy that usually results from using single sensors for monitoring the condition of different structures, I have developed a multi-sensor fusion technique in this thesis that combines sensing modalities on different Limpets to achieve structural integrity monitoring.