# Unmanned Autonomous Intelligent System in 6G Non-Terrestrial Network
## 4 Application of UAV-Aided Non-Terrestrial Networks in UAIS  
An unmanned autonomous intelligent system (UAIS) [80; 81; 82; 83; 84; 85; 86; 87; 88] is defined as a metronic system capable of fulfilling universal tasks without or with limited human involvement. Typical UAIS include connected autonomous vehicles [89], swarm robot systems [90], unmanned aerial vehicles [91], unmanned ground vehicles, unmanned maritime vehicles [92], smart manufacturering systems [93; 94; 95; 96], agricultural robots [97; 98; 99; 100; 101], service robots, and medical robots [102; 103; 104]. These systems are increasingly dependent on the  
Figure 4: Illustration of UAV fire detection architecture. comprehensive application of artificial intelligence, data science, ubiquitous networks, and distributed computing to fulfill complex tasks and adapt to ever-changing environments. Compared to traditional rule-based automation systems, UAIS offers advanced capabilities such as autonomy, intelligence, and collaboration. It supports general-purpose tasks such as perception, autonomous decision making, reasoning, and collaboration [105; 106]. One of the key factors that facilitate the UAIS ecosystem is the development of low-latency, ultra-reliable, and high-volume wireless communication, supporting a growing range of unmanned ground vehicles, self-driving cars, maritime unmanned vehicles, mobile robotics, and more. UAIS has demonstrated a growing need for ubiquitous network connectivity to facilitate the exchange of information and the offloading of computational tasks to edge computing devices or cloud servers. In some instances, network connections may be unavailable due to inadequate communication infrastructure or communication congestion. The emergence of the NTN communication concept sheds new light on UAIS by providing ubiquitous network connection and mobile edge computing. On the other hand, UAIS can also be utilized to support NTN communication in a variety of ways. UAVs are typical UAIS platforms used to support NTN communication, while UGVs, USVs, and CAVs are all promising in performing communication coverage tasks in 6G NTN. The rise of artificial intelligence (AI) has played an important role in providing UAIS with advanced autonomy and decision-making capabilities. AI is utilized to enable systems that can learn from experience and adapt to diverse and complex environments, which is vital to applications of UAIS. With the rapid advancement of software and hardware, various deep learning/reinforcement learning algorithms along with computing platforms offer sufficient computation resources to UAIS applications. In addition, the emergence of multi-access edge computing and distributed computation offloading has greatly boosted the development of AI-based applications, especially UAIS, which can fulfill specific tasks, such as object detection/reorganization, decision-making, and autonomous navigation. While in practical applications of UAIS, massive computation resources and low latency connections are not always available and have many limitations in real-world scenarios [107; 108; 109; 110]. Typical communication requirements of the UAIS in NTN is illustrated in Table 1, which pose significant challenges for NTN communication. With the assistance of artificial intelligence, UAIS can become an organic part of the future intelligent NTN communication. Advancements in UAIS are increasingly emphasizing decentralization, ubiquitous connectivity, and collective intelligence, which are vital for supporting an elastic and self-adaptive network architecture. The new trend of UAIS development has put forward higher requirements for autonomous capabilities, as illustrated in the Table 2, which will support the ubiquitous coverage of wide areas.