Simultaneous localization and mapping (SLAM) techniques are widely researched, since they allow the simultaneous creation of a map and the sensors’ pose estimation in an unknown environment. Visual-based SLAM techniques play a significant role in this field, as they are based on a low-cost and small sensor system, which guarantees those advantages compared to other sensor-based SLAM techniques. The literature presents different approaches and methods to implement visual-based SLAM systems. Among this variety of publications, a beginner in this domain may find problems with identifying and analyzing the main algorithms and selecting the most appropriate one according to his or her project constraints. Therefore, we present the three main visual-based SLAM approaches (visual-only, visual-inertial, and RGB-D SLAM), providing a review of the main algorithms of each approach through diagrams and flowcharts, and highlighting the main advantages and disadvantages of each technique. Furthermore, we propose six criteria that ease the SLAM algorithm’s analysis and consider both the software and hardware levels. In addition, we present some major issues and future directions on visual-SLAM field, and provide a general overview of some of the existing benchmark datasets. This work aims to be the first step for those initiating a SLAM project to have a good perspective of SLAM techniques’ main elements and characteristics.

Organometallic chemistry has recently gained a lot of attention in the domain of plastic scintillators.Homogenously dispersed metal complexes in a polymer matrix can afford plastic scintillators with unseen abilities. Heavy atom loading is very attractive as it gives access to plastics with increased sensitivity towards elusive radiations such as gamma and neutron. But this comes with a drawback, as heavy atoms tend to quench fluorescence, hence decreasing the scintillation yield. We present here a comprehensive study of this phenomenon with bismuth and gadolinium complexes. We investigate the influence of the ligand nature by varying organometallic and fluorophore concentration to probe their interaction. We also propose an explanation of the difference in behavior between these two metals. These results were applied to the fabrication of large volume loaded plastic scintillators (4100 cm 3 ). Bismuth loaded scintillators displayed characteristics equivalent to lead loaded commercial materials, and gadolinium samples proved to be able to capture thermal neutrons and release gamma rays. of our optimization, large scale loaded PSs (4100 cm 3 ) were synthesized and characterized.

Abstract. This paper presents a complete custom full-digital instrumentation device that was designed for real-time neutron flux estimation, especially for nuclear reactor incore measurement using subminiature Fission Chambers (FCs). Entire fully functional small-footprint design (about 1714 LUTs) is implemented on FPGA. It enables real-time acquisition and analysis of multiple channels neutron's flux both in counting mode and Campbelling mode. Experimental results obtained from this brand new device are consistent with simulation results and show good agreement within good uncertainty. This device paves the way for new applications perspectives in real-time nuclear reactor monitoring.

Coarse-Grained Reconfigurable Architectures (CGRAs) are promising high-performance and power-efficient platforms. However, their uses are still limited because of the current capability of the mapping tools. This paper presents a new scalable efficient design flow to map applications written in high level language on CGRAs. This approach leverages on simultaneous scheduling and binding steps respectively based on a heuristic and an exact method stochastically degenerated. The formal graph model of the application, obtained after compilation, is backward traversed and dynamically transformed when needed to allow for a better exploration of the design space. Results show that our approach is scalable, finds most of the time the best solutions i.e. the mappings with the shortest latencies, achieves lowest failure rate in carrying out solutions, provides lower computation time and explores more efficiently the solution space than the state of the art methods.

We introduce a new approach to take into account the memory architecture and the memory mapping in behavioral synthesis. We formalize the memory mapping as a set of constraints for the synthesis, and defined a Memory Constraint Graph and an accessibility criterion to be used in the scheduling step. We present a new strategy for implementing signals (ageing vectors). We formalize the maturing process and explain how it may generate memory conflicts over several iterations of the algorithm. The final Compatibility Graph indicates the set of valid mappings for every signal. Several experiments are performed with our HLS tool GAUT. Our scheduling algorithm exhibits a relatively low complexity that permits to tackle complex designs in a reasonable time.

Mapping an application on a coarse grained reconfigurable architecture (CGRA) is a complex task which is still often completely or partially realized manually. This paper presents an automated synthesis flow based on simultaneous scheduling and binding steps. The proposed method uses a backward traversal of the formal model obtained after compilation and dynamically transforms it when needed. Our approach is compared with state of the art techniques and its interest is shown through the mapping of several applications from digital signal and image processing domain.

Illegal radioactive material transportation detection, by terrorist for example, is problematic in urban public transportation. Academics and industrials systems include Radiation Portal Monitor (RPM) to detect radioactive matters transported in vehicles or carried by pedestrians. However, today's RPMs are not able to efficiently detect a radioactive material in movement. Due to count statistic and gamma background, false alarms may be triggered or at the contrary a radioactive material not detected. The statistical false alarm rate has to be as low as possible in order to limit useless intervention especially in urban mass transportation. The real-time approach depicted in this paper consists in using a time correlated detection technique in association with a sensor network. It is based on several low-cost and large area plastic scintillators and a digital signal processing designed for signal reconstruction from the sensor network. The number of sensors used in the network can be adapted to fit with applications requirements or cost. The reconstructed signal is improved by comparing other approaches. This allows us to increase the device speed that has to be scanned while decreasing the risk of false alarm.In the framework of a project called SECUR-ED Secured Urban Transportation -European Demonstration, this prototype system will be used during an experiment in the Milan urban mass transportation.

This paper deals with a new generation of acquisition systems for nuclear instrumentation. This project, called PING aims at developing instrumentation devices in order to cover a wide range of nuclear measurements with single hardware architecture. More specifically, this device is well suited for neutron measurements. This system is based on a full digital signal processing free from any analog signal neither formatting nor processing. Digitized signals can then be processed for physical information extraction. The dedicated embedded signal processing software in Field Programmable Gate Array (FPGA) allows us to achieve versatile passive or active neutron measurements, or gamma spectrometry. First experimental results are reported in this article. Both gamma and neutron measurements performance are presented.