Self-Driving Car Perception Platform

自动驾驶汽车正在浮出水面，但在成为现实之前，还有很多研究要做。许多突出的技术挑战涉及向这些车辆灌输强大的感知能力，以便它们可能(i)知道自己在哪里，（ii）识别动态物体，以及（iii）了解周围世界的状态。虽然基于卫星的定位可以帮助完成第一项任务，但人们普遍认为，机载传感器将是全面解决这些感知任务所必需的。该项目建议购买一辆适合道路的研究车辆，配备几种不同类型的传感器（相机、激光测距仪、雷达、惯性测量单元）；该车辆将用于收集大型数据集，以提高自动驾驶汽车的感知能力。虽然存在一些这样的数据集（例如，由共同申请人Urtasun准备的著名的KITTI数据集-下载了10,000次，被全球300个研究小组使用），但这只是一个起点。多伦多拥有各种不同的季节条件（特别是冬季），使其成为推动自动驾驶汽车感知边界的独特测试区域。在不同条件下收集数据集对于推动这一领域的研究，并执行申请人及其工业/政府合作伙伴的研究目标是必要的。该项目代表了计算机科学系和应用科学与工程学院之间重要的新合作，必将成为展示多伦多大学和加拿大机器人研究的高调机制。

Self-driving cars are looming on the horizon, but there is still much research to be done before they become a reality. Many of the outstanding technical challenges involve imbuing these vehicles with robust perception so that they might (i) know where they are, (ii) recognize dynamic objects, and (iii) understand the state of the world around them. While satellite-based positioning can help with the first task, it is widely accepted that on-board sensors will be necessary to fully solve these perception tasks. This project proposes to acquire a roadworthy research vehicle instrumented with several different types of sensors (cameras, laser rangefinders, radar, inertial measurement units); the vehicle will be used to gather large datasets in order to advance the perceptive capabilities of self-driving cars. While some such datasets exist (e.g., the well-known KITTI dataset prepared by co­applicant Urtasun - downloaded 10,000 times, used by 300 research groups worldwide), this is only a starting point. Toronto enjoys a wide variety of different seasonal conditions (particularly winter), making it a unique test area to push the boundaries of self-driving car perception. Gathering datasets in varying conditions is necessary to push research in this area, and execute the research aims of the applicants and their industrial/government partners. This project represents an important and new collaboration between the Dept. of Computer Science and the Faculty of Applied Science and Engineering and will surely be a high-profile mechanism to showcase the University of Toronto and Canadian robotics research.