SmartBoomerang - Teach, Blog and Repeat for an Inspection Flying Robot

SmartBoomerang - 对检查飞行机器人进行教学、博客和重复

• 批准号: 131291
• 金额: $ 13.94万
• 依托单位: BLUE BEAR SYSTEMS RESEARCH LTD
• 依托单位国家: 英国
• 项目类别: Feasibility Studies
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=131291
• 关键词: SmartBoomerang; Teach; Blog; Repeat; Inspection

This project develops an autonomous path following capability (in the form of a sensor and algorithm kit) for aerial inspection robots used to remotely survey structures in sectors such as oil & gas, mining, energy, chemical processing, water and transport. Aerial robots have enormous potential to slash costs relative to manual inspections, which are equipment and manpower intensive and typically represent a large proportion of the recurring cost of a structure over its lifetime. Current generation robots are typically operated manually within line of sight of a remote operator; this project will develop a sensor and algorithm kit enabling such robots to automatically retrace their steps around a known structure using vision and learning, greatly speeding up repetitive surveys. A 3D visual feature map is generated and refined, and over subsequent missions a robot would use this map of the structure for autonomous visual navigation using a relocalisation approach, allowing it to reach and return from the areas to be inspected autonomously. The proposed robot combines the real-time full 3D visual mapping and relocalisation methods developed at the University of Bristol and flight control technology developed by Blue Bear.

该项目为空中检查机器人开发自主路径跟踪功能（以传感器和算法套件的形式），用于远程测量石油和天然气、采矿、能源、化学加工、水和运输等领域的结构。与手动检查相比，空中机器人具有巨大的削减成本的潜力，手动检查是设备和人力密集型的，通常占结构在其生命周期内经常性成本的很大一部分。当前一代机器人通常在远程操作员的视线范围内手动操作；该项目将开发一个传感器和算法套件，使此类机器人能够利用视觉和学习自动围绕已知结构回溯其脚步，从而大大加快重复调查的速度。生成并细化 3D 视觉特征图，在后续任务中，机器人将使用该结构图通过重定位方法进行自主视觉导航，使其能够自主到达和从要检查的区域返回。该机器人结合了布里斯托大学开发的实时全 3D 视觉映射和重定位方法以及 Blue Bear 开发的飞行控制技术。