Safe Navigation of Robots in a Dynamic and Uncertain World

机器人在动态和不确定的世界中安全导航

• 批准号: RGPIN-2019-04365
• 负责人: Barfoot, Timothy
• 金额: $ 4.66万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 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=713442
• 关键词: Safe; Navigation; Robots; Dynamic; Uncertain

Robotics is poised to revolutionize several aspects of our society in the coming years from the way we move people and things around to healthcare to manufacturing. In particular, mobile robotics technology has matured to the point that self-driving cars and unmanned aerial vehicles (a.k.a., drones) are being actively pursued by industry, from small startups to the world's technology giants. While some products will come to market in the next few years, they will not be fully autonomous, meaning they will not operate under all conditions that a human operator can handle. To achieve this, a great deal more research is needed. Real applications of mobile robots are challenging because the operating environment (e.g., our roadways, our skies, big warehouses) can be large, cluttered, dynamic, and unknown/uncertain. This means that the key autonomy functions, which include localization, mapping, planning, and control, must address these challenges. Within robotics, we have barely scratched the surface when it comes to making systems that can operate for very long periods of time without human assistance. This program of research will continue to tackle these long-term autonomy challenges associated with localization, mapping, planning, and control of mobile robots. In particular, we will address (i) robust localization, (ii) multi-object tracking and prediction, (iii) knowledge/uncertainty representation, and (iv) safe planning. Tackling these issues will require novel sensing modalities, new algorithms rooted in machine learning and control/estimation theory, exploitation of big data/cloud computing, and extensive field testing. We will create new autonomy software comprising all the key functions needed to navigate mobile robots through a dynamic and uncertain world. As we do so, we will work closely with industrial partners to transfer our technology to real-world applications such as warehouse robots, self-driving cars, and drone delivery systems. Canada is rapidly growing its capabilities in these areas and we hope to make big contributions in terms of the technology and people needed to shape the future.

机器人技术有望在未来几年内彻底改变我们社会的几个方面，从我们移动人和物的方式到医疗保健到制造业。特别是，移动的机器人技术已经成熟到自动驾驶汽车和无人驾驶飞行器（又名，无人机）正受到从小型初创公司到世界科技巨头的行业积极追捧。虽然一些产品将在未来几年内上市，但它们不会完全自主，这意味着它们不会在人类操作员可以处理的所有条件下运行。为了实现这一点，需要进行更多的研究。 移动的机器人的真实的应用具有挑战性，因为操作环境（例如，我们的道路、我们的天空、大仓库）可以是大的、杂乱的、动态的、未知的/不确定的。这意味着关键的自主功能，包括定位，绘图，规划和控制，必须解决这些挑战。在机器人技术领域，当涉及到制造可以在没有人类帮助的情况下长时间运行的系统时，我们几乎没有触及表面。 该研究计划将继续解决与移动的机器人的定位、映射、规划和控制相关的长期自主性挑战。特别是，我们将解决（i）鲁棒定位，（ii）多对象跟踪和预测，（iii）知识/不确定性表示，以及（iv）安全规划。解决这些问题将需要新的传感模式，基于机器学习和控制/估计理论的新算法，大数据/云计算的开发以及广泛的现场测试。 我们将创建新的自主软件，包括在动态和不确定的世界中导航移动的机器人所需的所有关键功能。在此过程中，我们将与工业合作伙伴密切合作，将我们的技术转移到现实世界的应用中，如仓库机器人、自动驾驶汽车和无人机交付系统。加拿大在这些领域的能力正在迅速增长，我们希望在塑造未来所需的技术和人才方面做出重大贡献。