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

用于无人地面车辆长期视觉导航的虚拟路网

• 批准号: 476565-2014
• 负责人: Barfoot, Tim
• 金额: $ 2.5万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=599515
• 关键词: Virtual; road; networks; long; term

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).

移动机器人技术在过去十年中快速发展，使自动化采矿、农业、安全与安保以及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，这将成为实现这一愿景的关键构件。到目前为止，该技术主要是在短时间段(即几天)的点对点路径上进行测试。