Counter tunnel exploration, mapping, and localization with an unmanned ground vehicle

Larson, Jacoby; Okorn, Brian; Pastore, Tracy H.; Hooper, David A; Edwards, Jim

doi:10.1117/12.2054340

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Visual methods can be used on most robotic platforms such as UGVs [107,132,133], driverless cars [134], UAVs [18,123,126,135,136], and AUVS [109,137]. This is due to the fact that visual methods are not affected by the non-systematic errors that wheel odometry suffers from, making vehicle navigation more immune to rough and slippery terrain conditions.…”

Section: Visual-based Methodsmentioning

confidence: 99%

Survey of unmanned subterranean exploration, navigation, and localisation

Martz

Al-Sabban

Smith

2020

IET cyber-systems robotics

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Subsurface networks include mining tunnels, caves, and the urban underground. Each of these environments presents a complex setting with significant challenges in exploration, exploitation, etc. Multiple hazards exist, including environmental and structural, and conditions degrade and change temporally. We present a survey of research in autonomy, networking and mobility focused on exploring and/or mapping subsurface networks in unpredictable and unexplored environments. The focus is on mining tunnels as a proxy subterranean environment; motivated by the proximity of the authors to the Bonita Peak Mining District; a Superfund site consisting of 48 historic mines which have contaminated soil, groundwater and surface water with heavy metals as a result of historic practices. The exploration and assessment of the mining tunnels for remediation efforts presents an extremely challenging problem in subterranean navigation. Arguably, the environment in question is the most extreme and challenging subterranean environment. Unmanned assets must enter to explore and re‐map the tunnels to assess safety for subsequent entrance by robots and/or humans for proper remediation. The survey is split into three categories — Locomotion, GPS‐denied navigation and localization, and Communication. It is concluded with a proposed design for a platform that addresses the difficulties of exploring an abandoned mine

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Section: Visual-based Methodsmentioning

confidence: 99%

Survey of unmanned subterranean exploration, navigation, and localisation

Martz

Al-Sabban

Smith

2020

IET cyber-systems robotics

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“…It is very costly, and the base cost is around USD 60,000 [25]. Besides this, shape-changing robots are common in tunnel exploration and have to change shape to overcome obstacles and enter narrow passageways [26]. Reconfiguration is always challenging in shape-transforming robots.…”

Section: Review Of Mobile Scout Vehiclesmentioning

confidence: 99%

Design of a Reconfigurable Crop Scouting Vehicle for Row Crop Navigation: A Proof-of-Concept Study

Schmitz

Badgujar

Mansur

et al. 2022

Sensors

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Pest infestation causes significant crop damage during crop production, which reduces the crop yield in terms of quality and quantity. Accurate, precise, and timely information on pest infestation is a crucial aspect of integrated pest management practices. The current manual scouting methods are time-consuming and laborious, particularly for large fields. Therefore, a fleet of scouting vehicles is proposed to monitor and collect crop information at the sub-canopy level. These vehicles would traverse large fields and collect real-time information on pest type, concentration, and infestation level. In addition to this, the developed vehicle platform would assist in collecting information on soil moisture, nutrient deficiency, and disease severity during crop growth stages. This study established a proof-of-concept of a crop scouting vehicle that can navigate through the row crops. A reconfigurable ground vehicle (RGV) was designed and fabricated. The developed prototype was tested in the laboratory and an actual field environment. Moreover, the concept of corn row detection was established by utilizing an array of low-cost ultrasonic sensors. The RGV was successful in navigating through the corn field. The RGV’s reconfigurable characteristic provides the ability to move anywhere in the field without damaging the crops. This research shows the promise of using reconfigurable robots for row crop navigation for crop scouting and monitoring which could be modular and scalable, and can be mass-produced in quick time. A fleet of these RGVs would empower the farmers to make meaningful and timely decisions for their cropping system.

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