Barrnon Limited Integrated Sort and Segregate Solution
Barrnon Limited Integrated Sort and Segregate Solution
批准号:
95851
负责人:
金额:
$7.63万
依托单位:
依托单位国家:
英国
项目类别:
Small Business Research Initiative
财政年份:
2021
资助国家:
英国
项目状态:
已结题
起止时间:
2021 至 --
中文摘要
在我们第一次参加SBRI竞赛时,Barrnon设计并提交了一个名为BIDS(Barrnon集成退役系统)的机器人解决方案。它可以用来表征和减少需要退役的放射性资产的规模。该公司的新机器人企业名为BLISSS(Barrnon Limited集成分类和分离系统),建立在以前工作的基础上。这是一个能够自动识别、表征、拾取和放置退役产生的各种碎片的系统。BLISSS结合了创新的视觉、传感、机器学习、机器人控制、算法和正式方法来分类、分离和验证用于废物出口的碎片--所有这些都符合核废料分类方法。BLISSS的革命性在于,它可以复制并从根本上提高人类工人在退役期间的能力--消除了在危险环境中人类操作人员对废物进行分类和分离的需要。这项技术允许识别物体,根据物质和放射性对物体进行表征,验证、操纵和自主放置;此外,系统还受到正式方法的保护--这是一种数学证明,证明系统正在做所需的事情,否则永远不能做其他事情,从而消除了增强智能和人为错误的不确定性。系统还将提高效率和有效性:*在工作面-BLISSS不会感到疲劳,不会感到无聊,不会受到危及生命的伤害,不需要更换个人防护用品,没有人类剂量限制,可以全天候以机器人和机器学习带来的速度工作。*由于缺乏返工-幸福不会出现人为错误,由于正式的方法数学计算,它与1+1=2一样可预测。*由于记录保存-全部数字化、全部准确、全部编译、全部验证、始终。*由于算法派生的优化包装-系统扫描物品的外形系数和表面积,并将废物接受标准考虑在内。BLISSS不是特定于平台的。BIDS平台非常灵活,专为多工具、多传感器兼容性、即插即用而设计。然而,这种能力是通过将机器视觉、传感、机器学习和数学验证与专门为核细胞退役开发的硬件相结合而带来的。BLISSS与平台无关。它是一套程序和算法,当典型的退役硬件通过行业标准协议和语言通信时,可以使用这些程序和算法。
英文摘要
In our first SBRI competition entry, Barrnon designed and submitted a robotic solution called BIDS (the Barrnon Integrated Decommissioning System). It can be used to characterize and reduce the size of radioactive assets -- that need decommissioning.The company's new robotic venture is called BLISSS (Barrnon Limited Integrated Sort and Segregate System), building on this previous work. It is a system capable of autonomously identifying, characterizing, picking and placing various debris resulting from decommissioning. BLISSS brings together innovative vision, sensing, machine learning, robotic control, algorithms and formal methods to sort, segregate and verify debris for waste export -- all in accordance with nuclear waste category methodologies.BLISSS is revolutionary in that it can replicate, and radically improve on, the capabilities of a human worker during decommissioning - eliminating the need for human operatives in the hazardous environment to sort and segregate waste. The technology allows an object to be recognized, characterized in terms of substance and radioactivity, verified, manipulated and placed autonomously; also the system is protected by formal methods - a mathematical proof that the system is doing what is required and can _NEVER_ do otherwise, eliminating the uncertainty of augmented intelligence and human error.The system will also increase efficiency and effectiveness:* at the work-face - BLISSS doesn't get fatigued, doesn't get bored, doesn't get life threatening injuries, doesn't need to change out PPE, doesn't have a human dose limitation and can work at the pace brought by robotics and machine learning 24/7\.* due to lack of rework - BLISS does not make human errors, it is as predictable as 1+1=2 due to formal method mathematics.* due to record keeping - all digital, all accurate, all compiled, all verified, always.* due to algorithm derived optimized packing - the system scans the items for form factor and surface area and packs the items taking into consideration Waste Acceptance Criteria.BLISSS is not platform specific. The BIDS platform is flexible and is specifically designed for multiple tool, multiple sensor compatibility, plug and play. However the capability is brought by integrating machine vision, sensing, machine learning and mathematical verification with hardware specifically developed for nuclear cell decommissioning. BLISSS is agnostic to platform. It is a suite of programs and algorithms that can be utilized by typical decommissioning hardware as it communicates via industry standard protocols and languages.
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Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
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批准号:--
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项目类别:--
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资助金额:40万元
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批准年份:2020
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负责人:Vikrant Gupta
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依托单位: