**Acknowledgements**

*Use of Gamma Radiation Techniques in Peaceful Applications*

**5.3 Contour mapping behavior**

**Figure 20.**

estimation algorithm was calculated using the 1/*R*<sup>2</sup>

The swarm was restricted to move along the *x*-axis and the reference position generation was bound to ±0.5 m, in order to minimize risk of the swarm crashing into the walls of the flight volume. The tracking of the light source and three UAS platforms was carried out using the OptiTrack. Note that an embedded window to display source-seeking performance in real time using the motion capture system in the flight volume is shown in **Figure 19a**. **Figure 19b** shows how the UAS swarm's center moves as the source is moved. As expected, the oscillatory motion of the swarm's center occurs due to gradient estimation errors using a finite number of light sensors.

*(a) Contour mapping experiment with the swarm of three Crazyflie UAS (circled in green) and a virtual source (circled in red) along with a real-time data display window and (b) trajectory of the swarm's center.*

To demonstrate the effectiveness of the contour mapping algorithm in the indoor flight volume, three Crazyflie platforms were used. A virtual source was used due to a limited payload and communication capability of the Crazyflie UAS. As shown in **Figure 20a**, a virtual source was located on the ground and the OptitTrack tracked the source and each UAS in the swarm. The 'source strength' needed for the gradient

the virtual source position data from each UAS. **Figure 20b** shows the experimental results on a plot of motion of the swarm's center following the reference contour defined with respect to the virtual source located on the floor. It maps the reference

Ambient temperature CZT and CLYC sensors were integrated onto the UAS platform using the plug-and-play approach. The CZT sensor was designed for high resolution gamma spectroscopy. The CLYC sensor enables gamma and neutron measurements with an excellent neutron-gamma pulse shape discrimination with the figure of merit 2.3. The automated spectral analysis code locating peaks and

USB hardware connections were used to link the sensors and the main controller with the UAS power source. ROS was used for the data communication and data fusion. To streamline the process of bridging disparate components into a cohesive network, the collection of libraries describing the publisher/subscriber

contour within ±0.1 m, which is less than 8% of the size of the contour.

calculating their intensities was developed for both sensors.

model where *R* was obtained from

**102**

**6. Conclusion**

This work was supported by the Department of Energy Minority Serving Institution Partnership (MSIPP) managed by the Savannah River National Laboratory under SRNS contract MSIT00016.
