Lidar-Based Semantic Mapping of Indoor Environments

基于激光雷达的室内环境语义映射

• 批准号: 558367-2020
• 负责人: Kelly, Jonathan
• 金额: $ 2.48万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=723200
• 关键词: Lidar; Based; Semantic; Mapping; Indoor

Light detection and ranging (or lidar) sensors have revolutionized the nascent field of autonomous driving. The ability of lidar to generate accurate point cloud maps of the surrounding environment is essential to maintain situational awareness. Although lidar has primarily been deployed for self-driving vehicles to date, there are many other potential application areas. In particular, lidar can play an essential role in large-scale indoor mapping - the rich lidar data stream can be used to identify and track both known and novel objects indoors. Semantic maps, which contain information about individual object instances, are useful for inventory management in warehouses, for example.The Alliance research program will develop breakthrough capabilities in the area of lidar-based semantic mapping for warehousing and intralogistics applications. Intralogistics (which combines warehouse automation and logistics) is a $15 billion industry today and is expected reach $27 billion in size globally by 2025. In partnership with LeddarTech, Inc., the proposed Alliance research program will leverage machine learning to extract unique material and object signatures from lidar data streams in real time, improving the accuracy of semantic maps in cluttered indoor scenes. Enhanced semantic mapping capabilities will enable LeddarTech to enter new markets and to grow its offerings for existing markets, including the AV sector.

光检测和范围（或激光雷达）传感器已彻底改变了自动驾驶的新生场。 LIDAR生成周围环境的准确点云图的能力对于保持情境意识至关重要。尽管LIDAR主要是为迄今为止的自动驾驶汽车部署的，但还有许多其他潜在的应用领域。特别是，LiDar可以在大型室内映射中发挥重要作用 - 丰富的LIDAR数据流可用于识别和跟踪室内已知和新颖的对象。例如，包含有关各个对象实例的信息的语义图对于仓库中的库存管理很有用。联盟研究计划将在基于激光雷达的语义映射方面开发突破性功能，用于仓库和内部学术应用。 Intralogistics (which combines warehouse automation and logistics) is a $15 billion industry today and is expected reach $27 billion in size globally by 2025. In partnership with LeddarTech, Inc., the proposed Alliance research program will leverage machine learning to extract unique material and object signatures from lidar data streams in real time, improving the accuracy of semantic maps in cluttered indoor scenes.增强的语义映射功能将使Leddartech能够进入新市场，并为包括AV行业在内的现有市场增长其产品。