In order to increase the robustness of localisation and victim detection in low visibility situations it is necessary to fuse several sensors. The most common sensor used in robotics is the 2D laser scanner which delivers distance measurements. In combination with a camera the gained information can be supported by visual information about the environment. Thermal cameras are ideal for finding objects with a certain temperature, but they do not deliver distance information. The difficulty in fusing these two sensors is, that a correspondence between each distance measurement and its corresponding pixel within the thermal image needs to be found. As the laser scanner only displays one plane, this is not an intuitive task. A special triangular calibration target, covering all six degrees of freedom and being visible for both sensors, was developed. In the end the transformation between each laser scan point and its corresponding thermal image pixel is given. This allows for assigning every laser measurement within the field of view a corresponding thermal pixel. The final application will enable detection of human beings and display the distance required to reach them.

This paper describes the application of a weight estimation method for emergency patients in clinical environments. The approach applies established algorithms for point cloud processing and filtering to data from a low-cost, structured light sensor. A patient's volume is estimated on the basis of their visible front surface. The approach is currently being tested in the workflow of the emergency room at the Universitätsklinikum Erlangen, Germany. Preliminary results show the accuracy of the approach in relation to other conservative means of weight measurements, for example, by physicians and anthropometric measurements.