Inside Unmanned Systems

AUG-SEP 2018

Inside Unmanned Systems provides actionable business intelligence to decision-makers and influencers operating within the global UAS community. Features include analysis of key technologies, policy/regulatory developments and new product design.

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ENGINEERING. PRACTICE. POLICY. 57 August/September 2018 unmanned systems inside self through dark corridors looking for nuclear radiation. "We've built a flying vehicle that simultaneously 3-D maps and radiation maps in dark, GPS-denied airspace," Alexis said. This new work is part of a National Robotics Initiative project designed to help clean up 107 legacy sites of the Manhattan Project around the country that have been shuttered for decades. The data these robots gather will help the U.S. Department of Energy develop a cleanup plan for all these contaminated sites. For their experiments, the scientists built a hexarotor drone weighing just 2.6 kilograms (5.7 pounds). This prototype could f ly autonomously with the aid of a Pixhawk autopilot module for at- titude control and an Intel NUC5i7RYH mini PC computer to help it map its surroundings, control its position and plan its route. The radiation detector the scientists used on the robot was based on a Scionix V10B10 miniature thallium-doped cesium iodide scintillator crystal combined with a silicon photomultiplier and a light sensor. When gamma rays from radioactive material strike the scintillator, it gives off light the silicon photomultiplier can amplify enough for the sensor to detect. All in all, the entire radiation sensor weighed just 41 grams. "The scintillator is a consistent model we can trust in for years to come," Alexis said, "and through spectroscopic analysis of the radiation, it can not only tell the intensity of the radiation, but the type of material that produced it, such as cobalt, cesium or uranium." The prototype was equipped with a stereo cam- era, as well as LEDs to help it see in the dark, with the LEDs synchronized to f lash in time with the camera's shutter for the most efficient use of light. ROVIO (Robust Visual Inertial Odometry) software used data from the camera and an in- ertial measurement unit (IMU) to help perform odometry. Depth perception was achieved using either the stereo camera or LiDAR. "As we were carrying out this research, we had synergy with other projects we had involv- ing exploring mines and other subterranean en- vironments with drones, where dust or smoke can potentially degrade their vision," A lexis said. "The more degraded their vision becomes, the more we factor in uncertainty into collision avoidance. Another way we're dealing with dust or smoke is to work with thermal sensors that can help the drone see past such obstacles." Alexis and his colleagues tested their proto- type in both a lab and a train tunnel in Nevada. They placed radioactive samples of cesium-137 in both sites as the robot f lew around. Their UAS built 3-D maps of the environments, erring on the location of the radiation sources by about 25 centimeters, "which is still reasonably accurate enough," Alexis said. One challenge in working in underground environments "is that everything can look more or less the same," Alexis said. In such parame- ter-less environments, there are not that many details for the mapping software to use to indi- cate location. By working with multiple sensors, "the aim is to give the software something it can track," he noted. Alexis and his colleagues have moved from their prototy pe radiation-mapping drone to a modif ied DJI Matrix 100. While the initial SEEING IN THE DARK The University of Reno prototype used stereo cameras, LEDs and an inertial measurement unit (IMU) to help it navigate underground. " WE'VE BUILT A FLYING VEHICLE THAT SIMULTANEOUSLY 3-D MAPS AND RADIATION MAPS IN DARK, GPS-DENIED AIRSPACE." Kostas Alexis, head of the Autonomous Robots Lab, University of Nevada-Reno RADI ION CLEANUP

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