scholarly journals Detecting and Creating a 2D Heatmap of Radiation Hot Spots via Unmanned Ground Vehicle

2021 ◽  
Vol 8 (1) ◽  
pp. 31-36
Author(s):  
Natalie Hales ◽  
Spencer Lee ◽  
Edward Londner
Keyword(s):  
Research Design ◽  
Hot Spots ◽  
Indoor Environment ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Radiation Sources ◽  
The Creation ◽  
Initial Entry

The Army’s chemical, biological, radiological, nuclear, and explosives (CBRNE) units respond to the any threat involving CBRNE elements. Their missions often involve the search and identification of radiation sources in a compromised facility. A major concern with this mission is the survivability of the Initial Entry Team, who is tasked with surveying the volatile indoor environment for data. The creation of a system to assist in, and expediate, the process of initial entry will greatly increase the health and welfare of the team. In order to localize and detect radiation in a pot-entially contaminated indoor environment, our team will develop the RADBOT, an unmanned, tethered robot that can de-tect and map radiation. This paper will summarize the research, design, testing, and results for the development of the RADBOT system.

LOCALIZATION OF IONIZING RADIATION SOURCES VIA AN AUTONOMOUS ROBOTIC SYSTEM

2019 ◽  
Vol 186 (2-3) ◽  
pp. 249-256
Author(s):  
Tomas Lazna ◽  
Ota Fisera ◽  
Jaroslav Kares ◽  
Ludek Zalud
Keyword(s):  
Ionizing Radiation ◽  
Detection System ◽  
Region Of Interest ◽  
Robotic System ◽  
Unmanned Ground Vehicle ◽  
Localization Accuracy ◽  
Ground Vehicle ◽  
Autonomous Operation ◽  
Radiation Sources ◽  
Time Required

Abstract The article discusses an autonomous and flexible robotic system for radiation monitoring. The detection part of the system comprises two NaI(Tl) scintillation detectors: one of these is collimated to allow directionally sensitive measurements and the other is used to calculate the dose rate and provides sufficient sensitivity. Special algorithms for autonomous operation of an unmanned ground vehicle were developed, utilizing radiation characteristics acquired by the implemented detection system. The system was designed to operate in three modes: radiation mapping, localization of discrete sources and inspection of a region of interest. All of the modes were verified experimentally. In the localization mode, the time required to localize ionizing radiation sources was reduced by half compared to the field mapping mode exploiting parallel trajectories; the localization accuracy remained the same. In the inspection mode, the desired functionality was achieved, and the changes in the sources arrangement were detected reliably in the experiments.

Heterogeneous Bi-Directional Cooperative Unmanned Vehicles for Obstacle Avoidance

2016 ◽  
Author(s):  
Jonathan Lwowski ◽  
Liang Sun ◽  
Daniel Pack
Keyword(s):  
Obstacle Avoidance ◽  
Indoor Environment ◽  
Sliding Mode ◽  
Unmanned Vehicles ◽  
Unmanned Ground Vehicle ◽  
A Algorithm ◽  
Ground Vehicle ◽  
Cluttered Environment ◽  
Aerial View ◽  
Stable Sliding

In this paper, we present a novel bi-directional cooperative obstacle avoidance system of heterogeneous unmanned vehicles, consisting of an unmanned ground vehicle (UGV) and a microaerial vehicle (MAV), equipped with cameras, operating in an indoor environment without Global Positioning System (GPS) signals. The system demonstrates the synergistic relationship between the two platforms by sharing different perspectives and information collected independently using their on-board sensors in performing a navigation task in an indoor environment, including avoiding obstacles and entering narrow pathways. The MAV uses an aerial view of the environment to develop an obstacle free path for the UGV using the A* algorithm. The UGV deploys the planned path in conjunction with information gathered from its own front facing camera to navigate through a cluttered environment using a Lyapunov stable sliding mode controller. The UGV is responsible for detecting low and narrow pathways and to guide the MAV to move through them. The bidirectional cooperation has been tested in hardware as well as in simulation, showing the system’s effectiveness.

scholarly journals Fast Signals of Opportunity Fingerprint Database Maintenance with Autonomous Unmanned Ground Vehicle for Indoor Positioning

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3419 ◽  
Author(s):  
Yitang Peng ◽  
Xiaoji Niu ◽  
Jian Tang ◽  
Dazhi Mao ◽  
Chuang Qian
Keyword(s):  
Indoor Environment ◽  
Signal Strength ◽  
Indoor Positioning ◽  
Received Signal Strength ◽  
Kriging Interpolation ◽  
Unmanned Ground Vehicle ◽  
Received Signal Strength Indicator ◽  
Ground Vehicle ◽  
Fingerprint Database ◽  
Signals Of Opportunity

Indoor positioning technology based on Received Signal Strength Indicator (RSSI) fingerprints is a potential navigation solution, which has the advantages of simple implementation, low cost and high precision. However, as the radio frequency signals can be easily affected by the environmental change during its transmission, it is quite necessary to build location fingerprint database in advance and update it frequently, thereby guaranteeing the positioning accuracy. At present, the fingerprint database building methods mainly include point collection and line acquisition, both of which are usually labor-intensive and time consuming, especially in a large map area. This paper proposes a fast and efficient location fingerprint database construction and updating method based on a self-developed Unmanned Ground Vehicle (UGV) platform NAVIS, called Automatic Robot Line Collection. A smartphone was installed on NAVIS for collecting indoor Received Signal Strength Indicator (RSSI) fingerprints of Signals of Opportunity (SOP), such as Bluetooth and Wi-Fi. Meanwhile, indoor map was created by 2D LiDAR-based Simultaneous Localization and Mapping (SLAM) technology. The UGV automatically traverse the unknown indoor environment due to a pre-designed full-coverage path planning algorithm. Then, SOP sensors collect location fingerprints and generates grid map during the process of environment-traversing. Finally, location fingerprint database is built or updated by Kriging interpolation. Field tests were carried out to verify the effectiveness and efficiency of our proposed method. The results showed that, compared with the traditional point collection and line collection schemes, the root mean square error of the fingerprinting-based positioning results were reduced by 35.9% and 25.0% in static tests and 30.0% and 21.3% respectively in dynamic tests. Moreover, our UGV can traverse the indoor environment autonomously without human-labor on data acquisition, the efficiency of the automatic robot line collection scheme is 2.65 times and 1.72 times that of the traditional point collection and the traditional line acquisition, respectively.

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

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141775078 ◽  
Author(s):  
Tomas Lazna ◽  
Petr Gabrlik ◽  
Tomas Jilek ◽  
Ludek Zalud
Keyword(s):  
Gamma Radiation ◽  
Unmanned Aerial Vehicle ◽  
Human Operator ◽  
Spatial Gradient ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Area Of Interest ◽  
Radiation Sources ◽  
Aerial Vehicle ◽  
The Given

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.

Design and Realization of an All-terrain Unmanned Ground Vehicle

ROBOT ◽  
2013 ◽  
Vol 35 (6) ◽  
pp. 657 ◽  
Author(s):  
Taoyi ZHANG ◽  
Tianmiao WANG ◽  
Yao WU ◽  
Qiteng ZHAO
Keyword(s):  
Unmanned Ground Vehicle ◽  
Ground Vehicle
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