A Novel Architectural Design for Solving Lost-Link Problems in UAV Collaboration

G. Airlangga, Alan Liu
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Abstract

Research in unmanned aerial vehicles (UAVs) has gained attention from various communities because of their potential usage in improving safety and efficiency in different applications. An UAV has shown promising results in dangerous conditions such as forest fires, search and rescue, medical deliveries, wildlife monitoring and geophysical scanning. Some external conditions like slow or no internet connection areas such as rural, farm, forest, ocean, etc. may affect the performance of the UAVs. These conditions can be considered as lost-link problems. Several approaches have been conducted to resolve such issues by implementing robust on-board architecture, machine learning approaches and developing knowledge based reasoning systems. However, much of software architecture research has concentrated on UAV implementation in normal network condition. Thus, we propose a model for considering lost-link problems in software architecture. In this paper, we describe two interconnected architectures for client and server. The UAV as a client is controlled by microkernel based architecture and the server is developed using microservice architecture. Both of them are connected using a synchronizer component to collect, filter, analyze, predict, and mitigate an UAV when a lost-link problem occurs. Therefore, the UAV can still find an appropriate action to complete a mission as far as the sensor and actuator are not in a critical condition. Experiment results show that our approach yields high percentage of mission accomplishment, fault tolerance and performance in a lost-link situation.
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一种解决无人机协同失联问题的新架构设计
由于无人机在各种应用中具有提高安全性和效率的潜在用途,其研究受到了各界的关注。无人机在森林火灾、搜救、医疗运送、野生动物监测和地球物理扫描等危险条件下显示出了良好的效果。一些外部条件,如缓慢或没有互联网连接的地区,如农村,农场,森林,海洋等,可能会影响无人机的性能。这些情况可以被认为是失联问题。通过实现强大的板载架构、机器学习方法和开发基于知识的推理系统,已经采取了几种方法来解决这些问题。然而,很多软件架构的研究都集中在无人机在正常网络条件下的实现上。因此,我们提出了一个考虑软件体系结构中丢失链接问题的模型。在本文中,我们描述了客户端和服务器两种相互连接的体系结构。无人机作为客户端采用基于微内核的架构进行控制,服务器采用微服务架构进行开发。两者都使用同步器组件连接,以便在发生失联问题时收集、过滤、分析、预测和缓解无人机。因此,只要传感器和执行器不处于临界状态,无人机仍然可以找到合适的动作来完成任务。实验结果表明,该方法具有较高的任务完成率、容错性和失联情况下的性能。
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