Automotive Visual-inertial Navigation

汽车视觉惯性导航

基本信息

批准号：
555601-2020
负责人：
Forbes, James
金额：
$ 3.7万
依托单位：
McGill University
依托单位国家：
加拿大
项目类别：
Alliance Grants
财政年份：
2020
资助国家：
加拿大
起止时间：
2020-01-01 至 2021-12-31
项目状态：
已结题

来源：
https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=704947
关键词：
Automotive Visual inertial Navigation

项目摘要

An autonomous vehicle (AV) must use a suite of sensors, such as cameras and inertial sensors, to not only localize itself in the world, but also the positions of other vehicles, pedestrians, cyclists, and obstacles. The goal of the proposed research is to fuse measurements from various sensors, such as an inertial measurements unit (consisting of a rate gyroscope and an accelerometer), wheel odometer, as well as a monocular camera to design a simultaneous localization and mapping (SLAM) solution for AVs using automotive-grade hardware. The navigation solution must be able to estimate the position of static landmarks, such as road barriers and sign posts, and dynamic landmarks, such as moving vehicles, relative to the host vehicle. The navigation solution designed will be used as an input to a path-planning algorithm to plan paths for the AV around other vehicles and obstacles. As such, the development of a robust and reliable navigation solution is critical to the safety of the AV. The deployment of AVs is quickly becoming a reality in Canada and will have an enormous impact on the development of our economy, environment, and society. It is estimated that the cumulative potential benefits of AVs in Canada totals $65 billion dollars per year (expressed in 2013 Canadian dollars), including collision avoidance, fuel cost savings, and congestion avoidance. The proposed research will contribute to a rapidly expanding network of AV research in Canada. By contributing to research regarding the navigation solution for AVs, it is expected that the outcome of this research will place Canada closer to deploying AVs in Canadian cities.

自动驾驶汽车（AV）必须使用一套传感器，例如摄像机和惯性传感器，不仅将自己定位在世界上，而且还将其他车辆，行人，骑自行车的人和障碍物定位。拟议的研究的目的是融合来自各种传感器的测量值，例如惯性测量单元（由速率陀螺仪和加速度计组成），车轮里程表以及使用汽车级硬件的AVS的同时定位和映射（SLAM）解决方案。导航解决方案必须能够估计相对于主机车辆，例如路障和标志柱以及动态地标（例如移动车辆）的位置。设计的导航解决方案将用作路径规划算法的输入，以规划其他车辆和障碍物周围的AV路径。因此，强大而可靠的导航解决方案的开发对于AV的安全至关重要。 AVS的部署在加拿大迅速成为现实，将对我们的经济，环境和社会的发展产生巨大影响。据估计，加拿大AV的累积潜在利益每年总计650亿美元（以2013年加拿大美元表示），包括避免碰撞，节省燃油成本和避免拥塞。拟议的研究将为加拿大的AV研究网络迅速扩展。通过为AVS导航解决方案的研究做出贡献，可以预期这项研究的结果将使加拿大更接近在加拿大城市部署AV。