Virtual road networks for long-term visual navigation of unmanned ground vehicles

移动机器人技术在过去十年中发展迅速，使自动化采矿、农业、安全和自动驾驶汽车等应用成为近期现实。多伦多大学（UofT）一直在为无人地面车辆（ugv）开发一种视觉路线跟踪技术，该技术将成为实现这一愿景的关键组成部分。迄今为止，该技术主要是在短时间内（即几天）的点对点路径上进行的测试。该提案的主要目标是扩展这一核心技术，以允许定义整个虚拟道路网络（例如，数十公里的相互连接的路径），并在很长一段时间内（例如，数月或数年）用于各种服务应用中的ugv视觉导航。这将需要在几个领域取得重大进展，包括地图维护、强大的定位和动态路线规划。该项目将与位于加拿大的新兴的世界级无人驾驶汽车供应商Clearpath Robotics Inc.合作开展。导航技术的飞跃将使UofT能够在移动机器人的长期自主领域取得核心科学进步，并使Clearpath能够将这些进步纳入其未来的产品和解决方案中，从而扩大其客户群。

Mobile robotics technology has advanced at a rapid pace in the last decade, making applications such as automated mining, agriculture, safety & security, and self-driving cars a near-term reality. The University of Toronto (UofT) has been developing a visual route-following technique for Unmanned Ground Vehicles (UGVs) that will serve as a key building block to enable this vision. To date, the technique has been tested primarily on point-to-point paths over short periods of time (i.e., a few days).The main goal of this proposal is to extend this core technique to allow an entire virtual road network (e.g., tens of kilometres of interconnected paths) to be defined and used for visual navigation of UGVs in a variety of service applications over long periods of time (i.e., months or years). This will require major advances in several areas including map maintenance, robust localization, and dynamic route planning. The project will be carried out in partnership with Clearpath Robotics Inc., an emerging world-class provider of unmanned vehicles located in Canada.This leap forwards in navigation technology will allow UofT to make core scientific advances in the area of long-term autonomy for mobile robots and will allow Clearpath to incorporate these advances in their future products and solutions, thereby expanding their customer base.