Run the robot backward

Duckworth, Dexter; Shrewsbury, Brandon; Murphy, Robin R.

doi:10.1109/ssrr.2013.6719372

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…The localization accuracy of the method is limited to 4 cm. A rather different scheme is described by Duckworth et al 10 ; their source is localized inside a collapsed building, and the process strongly depends on the assistance from an operator. Eventually, it took a minute to localize the source inside a 6 Â 6 m 2 space.…”

Section: Discussionmentioning

confidence: 99%

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

Lázna

Gábrlík

Jílek

et al. 2018

International Journal of Advanced Robotic Systems

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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.

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Section: Discussionmentioning

confidence: 99%

“…Using UGVs in the discussed domain is demonstrated in articles. [6][7][8][9][10] A custom solution offering a high accuracy of the localization of gamma radiation hotspots is introduced within the present paper.…”

Section: Introductionmentioning

confidence: 99%

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

Lázna

Gábrlík

Jílek

et al. 2018

International Journal of Advanced Robotic Systems

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Autonomous Capabilities for Small Unmanned Aerial Systems Conducting Radiological Response: Findings from a High‐fidelity Discovery Experiment

Duncan

Murphy

2014

Journal of Field Robotics

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This article presents a preliminary work domain theory and identifies autonomous vehicle, navigational, and mission capabilities and challenges for small unmanned aerial systems (SUASs) responding to a radiological disaster. Radiological events are representative of applications that involve flying at low altitudes and close proximities to structures. To more formally understand the guidance and control demands, the environment in which the SUAS has to function, and the expected missions, tasks, and strategies to respond to an incident, a discovery experiment was performed in 2013. The experiment placed a radiological source emitting at 10 times background radiation in the simulated collapse of a multistory hospital. Two SUASs, an AirRobot 100B and a Leptron Avenger, were inserted with subject matter experts into the response, providing high operational fidelity. The SUASs were expected by the responders to fly at altitudes between 0.3 and 30 m, and hover at 1.5 m from urban structures. The proximity to a building introduced a decrease in GPS satellite coverage, challenging existing vehicle autonomy. Five new navigational capabilities were identified: scan, obstacle avoidance, contour following, environment‐aware return to home, and return to highest reading. Furthermore, the data‐to‐decision process could be improved with autonomous data digestion and visualization capabilities. This article is expected to contribute to a better understanding of autonomy in a SUAS, serve as a requirement document for advanced autonomy, and illustrate how discovery experimentation serves as a design tool for autonomous vehicles.

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Mobile robot for radiation mapping in indoor environment

Rahman

Sahari

Jalal

et al. 2020

IOP Conf. Ser.: Mater. Sci. Eng.

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Radiation mapping is the process of measuring radiation intensity level at distributed sampling points in a predefined region of interest (ROI). This procedure is crucial in any radiological related emergency to locate contamination hotspot(s) or in routine inspections in any radiation facilities. When workers knowingly enter a high radiation zone to perform radiation mapping, they are exposed to the risk of radiation exposure. Mobile robot is a potential solution that could eliminate the health and safety risk and subsequently improve the measurement accuracy. This paper reports implementation of mobile robot for radiation mapping by using a commercial mobile robot platform, Turtlebot2 in conjunction with Robot Operating System (ROS). Mobile robot is capable to generate physical map of the targeted environment by using Simultaneous Localization and Mapping (SLAM). Simultaneously, Geiger Muller detector is utilized to perform radiation measurement. The radiation data is directly plotted on the physical map hence the radiation intensity distribution throughout the ROI could be assessed. Functionality of the radiation mapping robot is evaluated in real-world experiments and the results will be presented in the paper.

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Run the robot backward

Cited by 5 publications

References 14 publications

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

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

Autonomous Capabilities for Small Unmanned Aerial Systems Conducting Radiological Response: Findings from a High‐fidelity Discovery Experiment

Mobile robot for radiation mapping in indoor environment

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