自重构异构机器人群的端到端设计

J. P. Queralta, L. Qingqing, Tuan Anh Nguyen Gia, Hong Linh Truong, Tomi Westerlund
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引用次数: 14

摘要

更广泛的应用要求机器人群在实际应用中更加灵活。在需要实时处理大量数据和需要高度态势感知的复杂场景中,仍然存在多种挑战。在现有的机器人群中,这个方向的选择是有限的,大多数同构机器人具有有限的操作和重构灵活性。我们通过将弹性计算技术和动态资源管理从边缘云计算领域引入群体机器人领域来解决这个问题。这支持在集群中为不同的应用程序动态提供集体功能。因此,我们将蜂群转换为能够处理复杂数据任务的分布式传感和计算平台,然后可以将其作为服务提供。特别是,我们讨论了如何将其应用于异构无人机群中的自适应资源管理,以及我们如何实现分布式数据处理算法的动态部署。基于可重构硬件和容器化服务的弹性无人机群,将有可能提高异质机器人群的自我意识、智能程度和自治水平。我们描述了协作感知的新方向,以及与机器人群交互的新方法。
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End-to-End Design for Self-Reconfigurable Heterogeneous Robotic Swarms
More widespread adoption requires swarms of robots to be more flexible for real-world applications. Multiple challenges remain in complex scenarios where a large amount of data needs to be processed in real-time and high degrees of situational awareness are required. The options in this direction are limited in existing robotic swarms, mostly homogeneous robots with limited operational and reconfiguration flexibility. We address this by bringing elastic computing techniques and dynamic resource management from the edge-cloud computing domain to the swarm robotics domain. This enables the dynamic provisioning of collective capabilities in the swarm for different applications. Therefore, we transform a swarm into a distributed sensing and computing platform capable of complex data processing tasks, which can then be offered as a service. In particular, we discuss how this can be applied to adaptive resource management in a heterogeneous swarm of drones, and how we are implementing the dynamic deployment of distributed data processing algorithms. With an elastic drone swarm built on reconfigurable hardware and containerized services, it will be possible to raise the self-awareness, degree of intelligence, and level of autonomy of heterogeneous swarms of robots. We describe novel directions for collaborative perception, and new ways of interacting with a robotic swarm.
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