Modern search and rescue workers are equipped with a powerful toolkit to address natural and man-made disasters. This introductory chapter explains how a new tool can be added to this toolkit: robots. The use of robotic assets in search and rescue operations is explained and an overview is given of the worldwide efforts to incorporate robotic tools in search and rescue operations. Furthermore, the European Union ICARUS project on this subject is introduced. The ICARUS project proposes to equip first responders with a comprehensive and integrated set of unmanned search and rescue tools, to increase the situational awareness of human crisis managers, such that more work can be done in a shorter amount of time. The ICARUS tools consist of assistive unmanned air, ground, and sea vehicles, equipped with victim-detection sensors. The unmanned vehicles collaborate as a coordinated team, communicating via ad hoc cognitive radio networking. To ensure optimal human-robot collaboration, these tools are seamlessly integrated into the command and control equipment of the human crisis managers and a set of training and support tools is provided to them to learn to use the ICARUS system.

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A new method for analysis of the active compound in a commercial pharmaceutical formulation in different steps of the production cycle, based on near-infrared diffuse reflectance spectroscopy, is proposed. The analysis includes three different steps of the production cycle: granules ready for compression (mixed phase), cores (intermediate) and coated tablets (final product). Satisfactory predictive results for production samples, independently of its origin in the production cycle, require calibration with laboratory-made samples covering the concentration range involved in the manufacturing process, and also production samples from various production batches and different steps, which introduce the variation sources inherent in such a process. A global and sole model was found to determine the active compound during the production cycle, with errors of prediction less than 1.8% in all cases. Tablets can be individually analysed with high accuracy and precision, so a content uniformity analysis may be performed.

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