Off-Road Multivehicle Autonomy for Challenging Outdoor Environments

应对具有挑战性的户外环境的越野多车辆自主性

• 批准号: 533392-2018
• 负责人: Marshall, Joshua
• 金额: $ 10.93万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Department of National Defence / NSERC Research Partnership
• 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=698466
• 关键词: Off; Road; Multivehicle; Autonomy; Challenging

This project is about studying and developing demonstrably practical methods and algorithms for reconnaissance activities using multiple robotic vehicles, with a particular focus on especially harsh and uncertain terrains (e.g., rocky, forested, unstructured, off-road) as well as on the problem of maintaining secrecy from potential intruders in such operations. The proposed research includes work on vehicle navigation, robot teaming, learning-based control, terrain assessment, as well as the concepts of opacity and unobservability for maintaining secrecy, where some vehicles may be only semi-autonomous, remotely driven, and/or supervised by human operators. In addition to this fundamental research, the project plan includes integration on actual mobile robots and field testing in representative environments. Although reconnaissance is the primary interest of the research partners associated with this project, it is anticipated that this research may also find application in other Canadian "off-road" scenarios, including mining automation, forestry, agriculture, as well is in planetary exploration and science. The proposed project also aims to provide unique HQP training experiences on multiple fronts. Student researchers will be given the opportunity to not only collaborate across several disciplines, but also take theory into practice by way of access to state-of-the-art mobile robots and field testing environments.

该项目是关于研究和开发可证明实用的方法和算法，用于使用多个机器人车辆进行侦察活动，特别关注特别恶劣和不确定的地形（例如，岩石，森林，非结构化，越野），以及在这种行动中保持对潜在入侵者的保密问题。拟议的研究包括车辆导航，机器人团队，基于学习的控制，地形评估，以及不透明和不可观察性的概念，以保持保密，其中一些车辆可能只是半自主，远程驾驶和/或由人类操作员监督。除了这项基础研究外，该项目计划还包括在实际移动的机器人上进行集成，并在代表性环境中进行现场测试。虽然侦察是与该项目有关的研究伙伴的主要兴趣，但预计这项研究也可能应用于加拿大其他“越野”方案，包括采矿自动化、林业、农业以及行星探索和科学。拟议项目还旨在在多个方面提供独特的HQP培训经验。学生研究人员将有机会不仅跨多个学科合作，而且通过访问最先进的移动的机器人和现场测试环境，将理论付诸实践。