Collaborative Technology Hardened for Underwater and Littoral Hazardous Environments

总部位于汉普郡范伯勒的英国跨国国防技术公司QinetiQ已与英国多家顶级创新技术提供商合作，以应对Innovate UK在极端和具有挑战性的环境中进行的机器人和人工智能研究与开发竞赛。该项目的标题是“克苏鲁”，以作家H。P·洛夫克拉夫特，一个被邪教崇拜的巨大实体。克苏鲁的外表被描述为像章鱼、龙和漫画般的人形。QinetiQ组建了一个全面的团队，适合应对与塞拉菲尔德现场正在运行的加工厂退役相关的复杂和广泛的挑战。该团队包括来自工业界和学术界的专业知识，专业领域包括：QinetiQ（牵头）、Nuvia UK Ltd、兰开斯特大学、布里斯托海事机器人和FORTIS远程技术;所有合作伙伴过去或目前已经与塞拉菲尔德有限公司合作，并在核退役管理局（NDA）的范围内就许多不同的退役相关项目进行合作，将互补的技术、系统、理解和技能结合起来，为极端环境提供解决方案，这些解决方案具有应用性，有些是跨领域的，该项目致力于研究和开发自主系统，利用最先进的机器学习技术，以促进危险（核）的自主检查和维护。空间。拟议的解决方案将提供以下创新组件：* 一个强大的机器人平台，是两栖的，具有更高的自主性，可在极端环境下操作，并具有24/7可用性。*基于声纳、触觉和无源光电传感器的同时定位和绘图（SLAM），使水下作业成为可能;能够使用新的快速透明深度学习图像分类器识别感兴趣的对象，在任务的背景下做出决定（检查和移动）包括碰撞检测和避免 * 触觉传感用于视觉模糊的环境，以实现详细的局部态势感知，以支持声纳传感。该平台将与一系列智能工具模块兼容，因此适用于一系列操作场景。"

"QinetiQ, a UK multinational defence technology company based in Farnborough, Hampshire, has teamed up with a number of the UK's top innovative technology providers in response to Innovate UK's Research and Developments competition for Robotics and Artificial Intelligence in extreme and challenging Environments. The title of the project is ""Cthulhu"" named after the cosmic entity created by writer H. P. Lovecraft, a gigantic entity worshipped by cultists. Cthulhu's appearance is described as looking like an octopus, a dragon and a caricature of human form.QinetiQ have assembled a comprehensive team suited for the complex and wide ranging challenges associated with the decommissioning of the active process plants on the Sellafield site. The team includes expertise from both industry and academia, and the fields of expertise include: QinetiQ (lead), Nuvia UK Ltd, University of Lancaster, Bristol Maritime Robotics and FORTIS Remote Technology ; all the partners have in the past or are currently already working with Sellafield Limited and also across the Nuclear Decommissioning Authority (NDA) estate on an number of diverse decommissioning related projects, bringing together complimentary technologies, systems, understanding and skills to deliver solutions for extreme environments that have application, some cross-cutting, Nationally and Internationally.This project undertakes research and the development of autonomous systems that exploit state of the art machine learning technologies in order to facilitate Autonomous Inspection and Maintenance of Hazardous (nuclear) Spaces.The proposed solution will deliver the following innovative components:* A robust robotic platform that is amphibious, with higher level of autonomy for extreme environment operations with 24/7 availability.* Simultaneous Localisation And Mapping (SLAM) based on sonar, tactile and passive Electro-optical (EO) sensors enabling underwater operations; able to recognise objects of interest using new fast transparent deep learning image classifiers, make decisions in the context of the task (inspect and move) including collision detection and avoidance* Tactile sensing for visually obscure environments to enable detailed local situational awareness to be achieved in support of the sonar sensing.* The platform will be compatible with a range of intelligent tooling modules and hence adaptable for a range of operational scenarios."