Cosmic rays interacting with the atmosphere result in a flux of secondary particles including muons and electrons. Atmospheric ray tomography (ART) uses the muons and electrons for detecting objects and their composition. This paper presents new methods and a proof-of-concept tomography system developed for the ART of low-Z materials. We introduce the Particle Track Filtering (PTF) and Multi-Modality Tomographic Reconstruction (MMTR) methods. Based on Geant4 models we optimized the tomography system, the parameters of PTF and MMTR. Based on plastic scintillating fiber arrays we achieved the spatial resolution 120 µm and 1 mrad angular resolution in the track reconstruction. We developed a novel edge detection method to separate the logical volumes of scanned object. We show its effectiveness on single (e.g. water, aluminum) and double material (e.g. explosive RDX in flesh) objects. The tabletop tomograph we built showed excellent agreement between simulations and measurements. We are able to increase the discriminating power of ART on low-Z materials significantly. This work opens up new routes for the commercialization of ART tomography.

This paper presents a feasibility study on the usage of Uppaal Timed Automata (UPTA) for deliberative level robotic control. The study is based on the Scrub Nurse Robot case-study. Our experience confirms that UPTA model based control enables the control loop to be defined and maintained during the robot operation autonomously with minimum human intervention. Specifically, in our robot architecture the control model is constructed automatically using unsupervised learning. Correctness of the model is verified on-the-fly against safety, reachability, and performance requirements. Finally, it is demonstrated that UPTA model based robot control, action planning and model updates have natural implementation based on existing model execution and conformance testing tool Uppaal Tron.

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