Cooperation between an unmanned aerial vehicle and an unmanned ground vehicle in highly accurate localization of gamma radiation hotspots

Abstract

This article discusses the highly autonomous robotic search and localization of radiation sources in outdoor environments. The cooperation between a human operator, an unmanned aerial vehicle, and an unmanned ground vehicle is used to render the given mission highly effective, in accordance with the idea that the search for potential radiation sources should be fast, precise, and reliable. Each of the components assumes its own role in the mission; the unmanned aerial vehicle (in our case, a multirotor) is responsible for fast data acquisition to create an accurate orthophoto and terrain map of the zone of interest. Aerial imagery is georeferenced directly, using an onboard sensor system, and no ground markers are required. The unmanned aerial vehicle can also perform rough radiation measurement, if necessary. Since the map contains three-dimensional information about the environment, algorithms to compute the spatial gradient, which represents the rideability, can be designed. Based on the primary aerial map, the human operator defines the area of interest to be examined by the applied unmanned ground vehicle carrying highly sensitive gamma-radiation probe/probes. As the actual survey typically embodies the most time-consuming problem within the mission, major emphasis is put on optimizing the unmanned ground vehicle trajectory planning; however, the dual-probe (differential) approach to facilitate directional sensitivity also finds use in the given context. The unmanned ground vehicle path planning from the pre-mission position to the center of the area of interest is carried out in the automated mode, similarly to the previously mentioned steps. Although the human operator remains indispensable, most of the tasks are performed autonomously, thus substantially reducing the load on the operator to enable them to focus on other actions during the search mission. Although gamma radiation is used as the demonstrator, most of the proposed algorithms and tasks are applicable on a markedly wider basis, including, for example, chemical, biological, radiological, and nuclear missions and environmental measurement tasks.

Calibration and accuracy assessment in a direct georeferencing system for UAS photogrammetry

“…Such a situation usually occurs in areas inaccessible or dangerous to humans, including zones of natural disasters, radiation hotspot localisation, or environmental mapping. The system was successfully employed in a gamma radiation mapping experiment which examined the potential of cooperation between UAS and UGV during the localisation of hotspots; the outcomes are presented in Lazna et al (2018) and Lazna et al (2017). …”

State-of-the-Art Mobile Radiation Detection Systems for Different Scenarios

“…A cooperative approach between a UGV and UAV was also proposed by Lazna et al in order to combine the advantages of both platforms [ 136 ]. In this case, the UAV uses (e.g., multi-rotor) photogrammetric techniques to generate a 3D map of the region of interest (ROI) (terrain reconstruction), to assist the UGV (which carry a radiation detector) in the path planning to find a hotspot.…”

Double Q-Learning for Radiation Source Detection

“…Hutchinson et al, sequentially determined the detector’s placement positions using the concept of maximum entropy sampling [ 18 ]. Lazna et al, proposed a circular path planning strategy to exploit the directional characteristics of detectors [ 19 ]. Ristic et al, designed the survey path incrementally by choosing detector positions and detection times maximizing the information gain in the Renyi divergence sense [ 20 ].…”