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This paper presents fast procedures for thermal infrared remote sensing indark, GPS-denied environments, such as those found in industrial plants such asin High-Voltage Direct Current (HVDC) converter stations. These procedures arebased on the combination of the depth estimation obtained from either a1-Dimensional LIDAR laser or a 2-Dimensional Hokuyo laser or a 3D MultiSenseSLB laser sensor and the visible and thermal cameras from a FLIR Duo Rdual-sensor thermal camera. The combination of these sensors/cameras issuitable to be mounted on Unmanned Aerial Vehicles (UAVs) and/or robots inorder to provide reliable information about the potential malfunctions, whichcan be found within the hazardous environment. For example, the capabilities ofthe developed software and hardware system corresponding to the combination ofthe 1-D LIDAR sensor and the FLIR Duo R dual-sensor thermal camera is assessedfrom the point of the accuracy of results and the required computational times:the obtained computational times are under 10 ms, with a maximum localizationerror of 8 mm and an average standard deviation for the measured temperaturesof 1.11 degree Celsius, which results are obtained for a number of test cases.The paper is structured as follows: the description of the system used foridentification and localization of hotspots in industrial plants is presentedin section II. In section III, the method for faults identification andlocalization in plants by using a 1-Dimensional LIDAR laser sensor and thermalimages is described together with results. In section IV the real time thermalimage processing is presented. Fusion of the 2-Dimensional depth laser Hokuyoand the thermal images is described in section V. In section VI the combinationof the 3D MultiSense SLB laser and thermal images is described. In section VIIa discussion and several conclusions are drawn.

Fusion of Real Time Thermal Image and 1D/2D/3D Depth Laser Readings for Remote Thermal Sensing in Industrial Plants by Means of UAVs and/or Robots