\chapter*{Conclusion}
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\addcontentsline{toc}{chapter}{Conclusion}

In the first chapter, I have compiled a description of basic principles of radiation detection. I focused primarily on scintillation detectors, because their parameters best fit to the desired ones. Scintillators typically have both higher density and higher volume than other types of detectors, therefore their probability of interaction with gamma radiation is higher than in case of gas-filled detectors or semiconductor detectors. The sensitivity of the detector is crucial due to relatively large assumed distance from the sources of gamma radiation until they are found. A possible way to realize direction-sensitive system is discussed in the thesis.

The next chapter focuses on development of a complex system that can be used for testing localization algorithms. The system is based on reconnaissance robot Orpheus-X3 developed by Group of Robotics and AI at the Faculty of Electrical Engineering and Communication, Brno University of Technology. The robot may be equipped with RTK-GNSS receiver that provides precise self-localization. A module developed by Ing. Tomáš Jílek, Ph.D.  is used for navigation and may be controlled externally by setting sequence of waypoints. A pair of scintillation detectors is used for measurement of the gamma radiation. I have created a library for communication with multichannel analyzers connected to the detectors. The sensory equipment is attached to the robot by custom mounting that I designed and made, using a 3D printer. Then I have developed software that periodically receives data from GNSS receiver and provides time synchronization for the multichannel analyzers. It also enables tracking the robot’s motion along planned trajectory and invoke its update in defined moments. For setting the control software, I proposed a structure of a configuration file and implemented a parser for it.

I took an existing algorithm for mapping a distribution of a radiation field which was applicable in rectangular areas, and extended it to a more general polygonal area. It is based on a trajectory composed of parallel lines. I have designed a method for autonomous localization of radiological sources in the resulting radiation map. It is composed of custom detector of two-dimensional local maxima and interpolation function. The mapping is a time consuming process, therefore I suggested an alternative algorithm that evaluates measured data in real time, and enables altering of the trajectory in order to get near the source faster. It is applicable in a situation where more than one strong source is present in the area of interest. When there is no strong source, the result of the algorithm is the same as in case of mapping.

The chosen geometry of the system provides directional sensitivity which I quantified experimentally. I have improved the directional characteristics by placing a lead shielding between detectors. That gave me access to development of more intelligent localization algorithms. I suggested a circle as a basic geometric primitive for initial exploration because it is more suitable for estimation of a direction in which the source can be found, than a line used in the previous algorithms. 	I developed them incrementally, beginning with the easiest case and ending with the most sophisticated solution. I proposed a method that allows estimating the direction of multiple sources from data collected on a circle. Once the direction is known, the robot may follow it. Under those conditions I suggested, the direction is continuously updated in order to localize the source as precisely as possible. The first three circular algorithms are based purely on estimation of the direction. The last one fuses directional information from multiple circles in order to get estimation of location of the sources. The directional information is described by rays which intersect in some points. I have designed a filter that lets pass only intersections that could correspond with a source.

I have developed a simulation suite for MATLAB that allowed me to test algorithms in the laboratory first. It helped me to find optimal values of several parameters which affect the behavior of the proposed algorithms. In simulation, all the algorithms worked as expected.

It is not feasible to include effects such as background contribution, motion and response of detectors, or kinematics of the robot into simulations all at once. Therefore, the algorithms need to be tested in real conditions with actual radiological sources as well. I implemented and integrated them all in the previously mentioned software creating an extensive control module. Then I tested them sequentially. Some of the assumptions based on simulations were disproved and both the program and parameters had to be altered to some extent. Eventually, all the algorithms provided satisfactory results except the last one – I have accomplished only a partial success with it. In the last section, I compared my algorithms regarding time efficiency and precision of localization. It is not possible to choose a single algorithm as the best one, since each provides better results in different situations.

I plan to continue in this research within my PhD studies. This area of research provides extensive area for further development. The proposed algorithms may exceed the state-of-the-art ones to some extent but there is still a lot work to do.

First, it is necessary to finish the last circular algorithm which covers the most cases but it has not been successfully tested yet. If proved efficient, it would signify that the circular algorithms are perspective. The next step would be a development of an algorithm that generates parameters of the circles optimally, given the definition of polygon and range of the detectors. Different types of detectors and geometries of a detector system should be tried and compared to the current solution. Even the mapping algorithm may be improved to be applicable in all types of polygons, even the ones with holes. At this point, only the point sources are assumed. It would be challenging to focus also on localization of line and area sources. 