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Cohort: Critical Science

机译:同类群组:批判科学

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摘要

Unmanned vehicle systems is an attractive technology for the military, but whose promises have remained largely undelivered. There currently exist fielded remote controlled UGVs and high altitude UAV whose benefits are based on standoff in low complexity environments that require sufficiently low control reaction time to allow for teleoperation. While effective within there limited operational niche such systems do not meet with the vision of future military UxV scenarios. Such scenarios envision unmanned vehicles operating effectively in complex environments and situations with high levels of independence and effective coordination with other machines and humans pursing high level, changing and sometimes conflicting goals. While these aims are clearly ambitious they do provide necessary targets and inspiration with hopes of fielding near term useful semi-autonomous unmanned systems. Autonomy involves many fields of research including machine vision, artificial intelligence, control theory, machine learning and distributed systems all of which are intertwined and have goals of creating more versatile broadly applicable algorithms. Cohort is a major Applied Research Program (ARP) led by Defence R&D Canada (DRDC) Suffield and its aim is to develop coordinated teams of unmanned vehicles (UxVs) for urban environments. This paper will discuss the critical science being addressed by DRDC developing semi-autonomous systems.
机译:无人驾驶车辆系统对军方来说是一种有吸引力的技术,但其承诺仍未兑现。当前存在现场遥控UGV和高空无人机,其优点是基于在要求足够短的控制反应时间以允许远程操作的低复杂度环境中的防区撞。尽管这些系统在有限的经营领域内很有效,但仍无法满足未来军事UxV方案的构想。这样的场景设想了无人驾驶车辆在复杂的环境和情况下能够高效运行,具有高度的独立性,并且与追求高水平,不断变化甚至有时相互冲突的目标的其他机器和人员进行有效协调。尽管这些目标雄心勃勃,但它们确实提供了必要的目标和灵感,并希望能在短期内使用有用的半自主无人系统。自治涉及许多研究领域,包括机器视觉,人工智能,控制理论,机器学习和分布式系统,所有这些领域相互交织,其目标是创建更通用的,广泛适用的算法。同类群组是由加拿大国防研发部(DRDC)Suffield领导的一项主要应用研究计划(ARP),其目的是为城市环境发展协调无人驾驶车辆(UxV)的团队。本文将讨论DRDC开发半自治系统所要解决的关键科学。

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