The detection of buried landmines using probing robots

Dawson‐Howe, Kenneth M.; Williams, T.G.

doi:10.1016/s0921-8890(98)00010-4

Cited by 20 publications

(12 citation statements)

References 2 publications

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“…An Am-Be neutron source as an isotropic source has been used with neutron spectrum shown in Figure 1 [11]. The neutron source which is 12 cm in length and 3 cm in diameter was located horizontally in the box of water with dimensions of 60 × 60 × 24 cm 3 . Distance of the box of water and the surface of soil is 1 cm.…”

Section: Methodsmentioning

confidence: 99%

“…Distance of the box of water and the surface of soil is 1 cm. A landmine (TNT) in cylindrical geometry, 5 cm in radius and 5 cm in height, was embedded at 5 cm depth from the surface of soil with dimensions of 60 × 60 × 11 cm 3 . NaI(Tl) 3 × 3 detector was positioned at the center of water box to take the spectrum of photons (Figure 2) [12].…”

Section: Methodsmentioning

confidence: 99%

“…During the recent years many efforts have been made to improve nuclear methods for the detection of landmines [1][2][3][4][5][6][7][8]. The most important advantage of methods based on neutron reactions is that neutrons have high penetration ability and the detection of landmines is possible even when they are hidden at the high depth.…”

Section: Introductionmentioning

confidence: 99%

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Investigation the Effects of Neutron Source Number and Arrangement in Landmines Detection by Thermal Neutron Capture Gamma Ray Analysis

Shiramin¹,

Masoudi²

2012

WJNST

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Thermal neutron capture can be used as a successful technique for detection of non-metallic landmines via the detection of their constituent like nitrogen. Recently, it has been shown that the detection of 10.829 MeV photons from the 14 N(n,γ) 15 N reaction can be used for finding the landmines. In this method a high-energy neutron source like 241 Am-Be inside water as a moderator is used to have thermal neutron. In this paper we have investigated the effects of the number of neutron sources and their orientation on the gamma ray spectrum by using MCNP4C code. The best case for number of sources and their positions and orientations have been achieved corresponding to maximum flux of 10.829 MeV photons.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Investigation the Effects of Neutron Source Number and Arrangement in Landmines Detection by Thermal Neutron Capture Gamma Ray Analysis

Shiramin¹,

Masoudi²

2012

WJNST

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“…Sub-surface sensing tasks are usually carried out using GPRs. So far, corresponding research work mainly focused on applications such as measuring the makeup and content of the soil [17], [18], locating underground structures [19], mapping archaeological features [20], or landmine detection [21], [22]. Similarly, GPR deployment on robots mainly focused on data collection tasks such as autonomous surveys [23], [24], inspection [25], or lunar crust analysis [26].…”

Section: Related Workmentioning

confidence: 99%

Autonomous Navigation in Inclement Weather Based on a Localizing Ground Penetrating Radar

Ort

Gilitschenski

Rus

2020

IEEE Robot. Autom. Lett.

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Most autonomous driving solutions require some method of localization within their environment. Typically, onboard sensors are used to localize the vehicle precisely in a previously recorded map. However, these solutions are sensitive to ambient lighting conditions such as darkness and inclement weather. Additionally, the maps can become outdated in a rapidly changing environment and require continuous updating. While LiDAR systems don't require visible light, they are sensitive to weather such as fog or snow, which can interfere with localization. In this letter, we utilize a Ground Penetrating Radar (GPR) to obtain precise vehicle localization. By mapping and localizing using features beneath the ground, we obtain features that are both stable over time, and maintain their appearance during changing ambient weather and lighting conditions. We incorporate this solution into a full-scale autonomous vehicle and evaluate the performance on over 17 km of testing data in a variety of challenging weather conditions. We find that this novel sensing modality is capable of providing precise localization for autonomous navigation without using cameras or LiDAR sensors. Index Terms-Autonomous vehicle navigation, field robots, wheeled robots, intelligent transportation systems. I. INTRODUCTIONR OBUST localization in diverse conditions is a key challenge to enable the widespread deployment of autonomous vehicles. Since relying purely on a global navigation satellite system (GNSS), such as the Global Positioning System (GPS) does not provide sufficient precision, research and industry efforts have focused primarily on utilizing cameras and laser scanners for the navigation task. These systems typically use Simultaneous Localization and Mapping (SLAM) algorithms [1] for creating and maintaining maps of the environment that allow for highly precise localization and navigation.Using vision and laser sensors as localization sources comes with its own set of challenges. For instance, localization from purely visual maps needs to account for the fact that, even in the absence of occlusions, the appearance of the environment strongly varies depending on weather, season, time of day, and a potentially changing environment [2]. While laser scanners

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“…In this situation, it is usually not possible to provide the required quality of landmine detection by sensing only one of the landmine characteristics. Thus, there have been developments of sensing devices using different physical principles (appropriate to the landmine characteristics) (Dawson-Howe and Williams, 1998), in order to provide as much information as possible. A combination of the characteristic and the sensing method defines a type of signature that a specific detector acquires from the landmine.…”

Section: Landmine Recognition On a Mobile Robotmentioning

confidence: 99%