Multi-UAV Active Simultaneous Localization and Mapping in Unknown Indoor Environments

未知室内环境下多无人机主动同步定位与建图

• 批准号: 576966-2022
• 负责人: Berkane, SoulaimaneS
• 金额: $ 3.28万
• 依托单位: Québec en Outaouais
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=757365
• 关键词: Multi; UAV; Active; Simultaneous; Localization

Nowadays, unmanned aerial vehicles (UAVs) (also known as drones) are becoming crucial in countless applications. However, most of the traditional commercial drones are remotely piloted or semi-autonomous which places obstacles in the way of their efficient deployment in challenging conditions and time-critical missions (e.g., search and rescue). Fortunately, with the unceasing development of lightweight sensing and sophisticated real-time computing, drones can now be designed to self-perceive and make autonomous decisions during the execution of tasks. Yet, the next generation of UAVs will be living up to the hype only if we are able to successfully and efficiently deploy fleets of fully autonomous UAVs to accomplish even more complex missions and tasks. In fact, multiple drones can be deployed to speed up complex missions while collaboratively mapping and exploring an unknown environment. Collaboration not only accelerates the mapping and exploration process but also minimizes uncertainty in decision making. This research project aims at addressing several challenges related to the design of efficient and reliable localization, mapping, and exploration algorithms for multi-UAV systems navigating in unknown indoor environments. In particular, the challenge consists in deploying a fleet of UAVs, relaying on vision and inertial systems and endowed with limited on-board computational power, to autonomously navigate and map a completely unknown environment as fast and efficiently as possible. Our proposed solution for this technology challenge consists in the amalgamation of different approaches in control systems and robotics at different levels to coordinate the group of UAVs to accomplish this mission. The accomplishment of the research goals outlined in this project will open doors to new and exciting applications for fully autonomous multi-UAV systems operating in tangled environments. This project is also an excellent opportunity to train highly qualified professionals in these promising fields who can become leaders in research and technology, sustaining Canada's economic growth.

如今，无人驾驶汽车（无人机）（也称为无人机）在无数应用中变得至关重要。但是，大多数传统的商业无人机都是远程试验或半自治的，这会以其有效部署在有挑战性的条件和关键时期任务（例如搜索和救援）中的有效部署。幸运的是，随着轻巧感测和复杂的实时计算的不断发展，无人机现在可以设计为自我感知并在执行任务期间做出自主决策。但是，只有在我们能够成功地部署完全自主无人机的车队以完成更复杂的任务和任务时，下一代无人机才能达到炒作。实际上，可以部署多个无人机来加快复杂任务，同时协作映射和探索未知的环境。协作不仅加速了映射和探索过程，而且还可以最大程度地减少决策的不确定性。该研究项目旨在解决与在未知室内环境中导航的多UAV系统的高效且可靠的本地化，映射和探索算法的设计有关的挑战。特别是，挑战在于部署无人机车队，传达视觉和惯性系统，并具有有限的板载计算能力，以自主浏览和绘制尽可能快，有效地绘制完全未知的环境。我们针对该技术挑战的建议解决方案包括在不同级别的控制系统和机器人技术中的不同方法融合，以协调无人机群以完成这一任务。该项目中概述的研究目标的实现将为在纠结环境中运行的完全自主的多UAV系统打开大门。该项目也是一个很好的机会，可以在这些有前途的领域培训高素质的专业人士，这些领域可以成为研究和技术领域的领导者，从而维持加拿大的经济增长。