I-Corps: Delivering Integrated Technology for Automated Wide-Area Humanitarian Mine Action Surveys

I-Corps：为自动化广域人道主义排雷行动调查提供集成技术

• 批准号: 2313759
• 负责人: Alex Nikulin
• 金额: $ 5万
• 依托单位: SUNY at Binghamton
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-15 至 2024-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2313759&HistoricalAwards=false
• 关键词: Corps; Delivering; Integrated; Technology; Automated

The broader impact/commercial potential of this I-Corps project is the development of technologies that effectively detect and clear landmines over wide surface areas. Humanitarian demining is the process where agencies (governmental or otherwise) survey a potentially hazardous area to detect, identify, and subsequently clear any explosive hazards (landmines or unexploded ordinance) in a post-conflict region. The goal of humanitarian demining is to release previously explosive-contaminated land back to impacted communities to allow the land to be used and developed without fear of injury and death caused by landmines and unexploded ordnance. The enormous variety of explosives, environments in which they lie, and conditions in which they may be found, create a multi-faceted problem that requires innovative technological solutions. This project is a demonstration of the powerful and wide-reaching capabilities of drones and machine learning in humanitarian mine action applications. The implementation of this technology will dramatically increase the rate and safety of demining, increasing the safety of demining operators, and allowing communities to reclaim previously inaccessible land for future development.This I-Corps project is based on the development of an integrated artificial intelligence-assisted unmanned aerial vehicle drone survey platform that a demining agency could quickly and effectively use to perform initial wide-area surveys. This technology will save money and time on subsequent demining activities in areas of critical contamination. The methods can be expanded to detect not only direct evidence of landmines and unexploded ordinances, but also indirect evidence such as explosion craters, minefield warning signs, or dead livestock potentially killed by explosives. Combining state-of-the-art deep learning technology, commercially available drones, and miniaturized optical sensors, this team created new solutions. This technology involves drone survey methods combined with innovative deep learning algorithms. The first step consists of integrating commercial visual light, thermal and multispectral drones to survey areas that are suspected to be contaminated with explosives. After the survey is complete, the deep learning method is used to generate the predicted coordinate locations of the explosives. In addition, a high-quality map of the suspected hazardous region is produced with each predicted explosive marked and labeled with its predicted class. The entire process takes place without using the internet, is user friendly, and can detect and classify most of the aerially-visible landmines and unexploded ordinances at a rate of 800 square meters per hour.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

I-Corps项目更广泛的影响/商业潜力是开发有效探测和清除大面积地雷的技术。人道主义排雷是各机构(政府或其他机构)对潜在危险区域进行调查，以发现、识别并随后清除冲突后地区的任何爆炸危险(地雷或未爆弹药)的过程。人道主义排雷的目标是将以前受爆炸物污染的土地释放回受影响的社区，使土地得以使用和开发，而不必担心地雷和未爆弹药造成的伤亡。爆炸物种类繁多，其所处环境和可能被发现的条件，造成了一个多方面的问题，需要创新的技术解决办法。该项目展示了无人驾驶飞机和机器学习在人道主义排雷行动应用中的强大和广泛能力。这项技术的实施将极大地提高排雷的速度和安全性，增加排雷操作员的安全，并使社区能够开垦以前无法进入的土地供未来发展。这一i-Corps项目基于开发一个集成的人工智能辅助的无人机无人机调查平台，排雷机构可以快速有效地利用该平台进行初步的大范围调查。这项技术将为随后在污染严重地区的排雷活动节省资金和时间。这些方法不仅可以扩大到检测地雷和未爆物品的直接证据，还可以检测间接证据，如爆炸坑、雷区警告标志或可能被炸药炸死的死亡牲畜。这个团队结合了最先进的深度学习技术、商用无人机和微型光学传感器，创造了新的解决方案。这项技术涉及无人机测量方法与创新的深度学习算法相结合。第一步包括整合商用可见光、热和多光谱无人机，以探测疑似受爆炸物污染的区域。在测量完成后，使用深度学习方法生成炸药的预测坐标位置。此外，还制作了疑似危险区域的高质量地图，每种预测的爆炸物都标上了其预测的等级。整个过程不使用互联网，用户友好，可以以每小时800平方米的速度探测和分类大多数空中可见的地雷和未爆炸条例。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。