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: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=737584
• 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.

从我们将人们和事物转移到医疗保健到制造业的方式中，机器人技术将在未来几年内彻底改变我们社会的几个方面。特别是，移动机器人技术已经成熟到自动驾驶汽车和无人驾驶汽车（又称无人机），该行业正在积极追求从小型初创公司到世界技术巨头的行业。尽管某些产品将在未来几年内推向市场，但它们不会完全自主，这意味着它们不会在人类运营商可以处理的所有条件下运行。为此，需要更多的研究。移动机器人的真实应用是具有挑战性的，因为操作环境（例如，我们的道路，我们的天空，大仓库）可能很大，混乱，动态且不知名/不确定。这意味着包括本地化，映射，计划和控制在内的关键自治功能必须应对这些挑战。在机器人技术中，我们在制造可以在没有人为援助的情况下可以长时间运行的系统时几乎没有刮擦表面。该研究计划将继续应对与移动机器人的本地化，映射，计划和控制相关的这些长期自治挑战。特别是，我们将解决（i）强大的本地化，（ii）多对象跟踪和预测，（iii）知识/不确定性表示以及（iv）安全计划。解决这些问题将需要新颖的传感方式，植根于机器学习和控制/估计理论的新算法，对大数据/云计算的开发以及广泛的现场测试。我们将创建新的自治软件，其中包括通过动态和不确定的世界导航移动机器人所需的所有关键功能。这样做，我们将与工业合作伙伴紧密合作，将我们的技术转移到现实世界中的应用程序，例如仓库机器人，自动驾驶汽车和无人机交付系统。加拿大在这些领域迅速增强了其能力，我们希望在塑造未来所需的技术和人们方面做出巨大贡献。