The three-dimensional reconstruction of radioactive hotspots poses a significant challenge during radiological characterization phases in environments that have undergone radiological or nuclear activity. The integration of ground or aerial robotic vectors during decontamination and decommissioning (D&D) operations of nuclear facilities emphasizes the crucial importance of developing such techniques. One contemplated approach to achieving this reconstruction involves merging radiological information from a gamma imager with visual data obtained through SLAM-like methods. The literature has already demonstrated the advantages of this combination. However, proposed solutions for addressing this challenge encounter integration difficulties with robotic vectors. The results obtained in thesis work conducted at SIMRI (Service for Instrumentation and Metrology of Ionizing Radiations) make it conceivable to develop a prototype imager meeting the needs of three-dimensional reconstruction of radioactive hotspots. Research on 3D reconstruction using the world's most compact coded-mask gamma imager (Nanopix), led by Kamel BENMAHI at LCIM, has showcased Nanopix's ability to locate radioactive hotspots in 3D within in-situ measurements. Andrea MACARIO BARROS's thesis work at LEMA has led to the development of SLAM methods associated with contamination measurements, integrated into a portable system, whose performance has been evaluated during on-site experimental campaigns. The objective of this thesis work is to develop a compact multimodal imager combining 3D gamma imaging localization techniques with SLAM techniques for applications related to the nuclear industry.
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