Simulator Driven Machine Learning on Embedded Systems for GPR Navigation and IED Detection, Akronym: MEDICI-LIBERTAD

用于探地雷达导航和简易爆炸装置检测的嵌入式系统上的模拟器驱动机器学习，缩写：MEDICI-LIBERTAD

• 批准号: 423771041
• 负责人: Dr.-Ing. Christoph Baer
• 金额: --
• 依托单位: Colciencias
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/423771041?language=en
• 关键词: Simulator; Driven; Machine; Learning; Embedded

Decades of guerilla warfare in Colombia have left behind a deadly legacy of thousands of landmines. In what could be a new start for Colombia, in 2016 the bloody civil war which raged intermittently for five decades was finally brought to an end. A long hoped-for peace agreement was signed between the government in Bogotá and guerilla group FARC. Prior to this, over 220,000 people were killed in conflicts between state security forces, left-wing rebels, and right-wing paramilitaries. Millions of people were also driven from their homes. Colombia now has the chance to improve its economy, political culture, and human rights and perhaps also rehabilitate its murky image abroad. But for the people of Colombia, everyday life is still marred by danger. The country is still peppered with landmines from the armed conflict with the guerilleros.The applied project “MEDICI-LIBERTAD” is one of two follow-up projects of “MEDICI”, which was funded by DFG (MU 3507/3-1, RO 2493/4-1, SA 1035/6-1 ) and Colciencias between 2014 and 2017. In order to face the great diversity in Colombian demining operations, due to altering surroundings and IED construction, the main objective of “MEDICI-LIBERTAD” is to investigate hardware embedded artificial neuronal networks in combination with sensor fusion approaches. This includes sensor fusion concepts for the positioning of a GPR device on the one hand and pattern recognition supported detection algorithms on the other hand. Regarding the required training data for the machine learning, massive and adequate data of numerous demining scenarios must be available. Here, the suitability of a self-written 2D-FDFD simulator will be investigated, which allows for randomized GPR-IED simulations including combined simulations with real and artificial data. The essential parts of the aimed objectives are described in the following.In the view of the collaboration partners, the proposed project has potential to improve the state of the art regarding both, hardware and software for neuronal network supported pattern recognition in GPR systems. Here, an optimized GPR-IED simulator is applied to generate the required teaching data for the machine learning.Since humanitarian demining operations are an important task within the peace process in Colombia, governmental and non-governmental organizations like HALO-Trust will support this project by evaluating the investigated procedures in actual mine–contaminated areas. Moreover, findings of the MEDICI projects will be directly included in the RADAR lecture, which is hold every year by the German partners in Colombia in order to guarantee a sustainable education of Colombia’s next generation engineers.

哥伦比亚数十年的游击战留下了数千枚地雷的致命遗产。2016年，哥伦比亚断断续续爆发了50年的血腥内战终于结束，这对哥伦比亚来说可能是一个新的开始。博戈塔政府和游击队组织哥伦比亚革命武装力量签署了一项期待已久的和平协议。在此之前，超过22万人在国家安全部队、左翼叛乱分子和右翼准军事组织之间的冲突中丧生。数百万人也被赶出家园。哥伦比亚现在有机会改善其经济、政治文化和人权状况，或许还能恢复其在国外的阴暗形象。但对哥伦比亚人民来说，日常生活仍然受到危险的破坏。由于与游击队的武装冲突，该国仍然遍布地雷。应用项目“MEDICI-LIBERRIGHTS”是“MEDICI”的两个后续项目之一，该项目由DFG（MU 3507/3-1，RO 2493/4-1，SA 1035/6-1）和Colciencias在2014年至2017年期间资助。 由于环境的改变和简易爆炸装置的建造，哥伦比亚排雷行动的多样性很大，为了应对这种情况，“MEDICI-LIBERRANCE”的主要目标是结合传感器融合方法研究嵌入硬件的人工神经网络。这包括传感器融合的概念，一方面定位的GPR设备和模式识别支持的检测算法的另一方面。关于机器学习所需的训练数据，必须提供大量排雷情景的大量和充分的数据。在这里，一个自写的2D-FDFD模拟器的适用性将进行调查，它允许随机GPR-IED模拟，包括结合模拟与真实的和人工数据。在合作伙伴看来，拟议的项目有可能改善最先进的硬件和软件的神经网络支持模式识别的GPR系统。由于人道主义排雷行动是哥伦比亚和平进程中的一项重要任务，政府和非政府组织，如HALO-Trust，将通过评估实际地雷污染地区的调查程序来支持这一项目。此外，MEDICI项目的研究结果将直接纳入雷达讲座，该讲座每年由德国合作伙伴在哥伦比亚举办，以确保哥伦比亚下一代工程师的可持续教育。