Unmanned Aerial Systems (UAS) have rapidly gained attraction in recent years as a promising solution to revolutionize numerous applications and meet the growing demand for efficient and timely delivery services due to their highly automated operation framework. Beyond Visual Line of Sight (BVLOS) operations, in particular, offer new means of delivering added-value services via a wide range of applications. This "plateau of productivity" holds enormous promise, but it is challenging to equip the drone with affordable technologies which support the BVLOS use case. To close this gap, this work showcases the convergence of the automotive and aviation industries to advance BVLOS aviation for UAS in a practical setting by studying a combination of Commercial Off-The-Shelf (COTS) technologies and systems. A novel risk-based approach of investigating the key technological components, architectures, algorithms, and protocols is proposed that facilitate highly reliable and autonomous BVLOS operations, aiming to enhance the alignment between market and operational needs and to better identify integration requirements between the different capabilities to be developed.

The deployment of autonomous robots in harsh and unpredictable environments has gained significant attention in recent years, driven by the need to improve safety and efficiency in tasks where human involvement poses significant risks. Technological advances in sensors and communication technologies, as well as the proliferation of AI, have catalysed the development of highly capable and robust robotic systems in diverse scenarios, optimising efficiency, particularly in the area of disaster response. However, despite the progress made in the field of autonomous Search and Rescue (SAR) operations in harsh environments, several challenges remain unresolved. This paper presents a comprehensive overview of the key technological advancements in components, algorithms and communication systems and how they facilitate highly efficient and robust autonomous missions in extreme subterranean conditions and SAR operations. Additionally, this paper aims to tackle some of the key challenges encountered during emergency response operations through a novel autonomous robotic design that leverages locomotion, perception, communication, and control capabilities to achieve effective exploration tasks in harsh and hazardous environments. Finally, it sets the scene for future enhancements in the area of autonomous and intelligent robots, suggesting potential avenues for further research and development in enhancing their capabilities and adaptability.

Commercial Unmanned Aircraft Systems (UAS) have a wide range of applications, including package delivery, inspection as well as search and rescue missions. To operate Unmanned Aircraft Vehicles (UAV) Beyond Visual Line of Sight (BVLOS), reliable long-distance communication is essential. Although the cellular network is a potential solution, it still faces issues such as signal loss and increased handover at higher altitudes. To mitigate these issues, our work proposes the usage of two cellular links from different providers, which are prioritised according to Quality of Service (QoS) prediction. We evaluate multiple AI-based model architectures for the prediction, and find that the model consisting of Gated Recurrent Units (GRU) and convolutional layers outperforms the others. The models are trained and tested on real-world data showing a reduction in latency peaks, thereby increasing connection resilience. Additionally, the prediction pipeline is designed to be executable on the UAV side and is not limited to a specific geographical area, making it applicable to real-world scenarios. Finally, we present a pre-flight path planning algorithm that considers QoS when calculating the flight path in order to further enhance the communication. To support the research community, we publicly share the dataset used to obtain our results.

Unmanned Aerial Systems (UAS) have rapidly gained attraction in recent years as a promising solution to revolutionize numerous applications and meet the growing demand for efficient and timely delivery services due to their highly automated operation framework. Beyond Visual Line of Sight (BVLOS) operations, in particular, offer new means of delivering added-value services through a wide range of applications. This ’plateau of productivity’ holds enormous promise but it is challenging to equip the drone with affordable technologies which support the BVLOS use-case. To close this gap, this work showcases the convergence of the automotive and aviation industries to advance BVLOS aviation for UAS in a practical setting by studying a combination of Commercial Off-The-Shelf (COTS) technologies and systems. A novel risk based approach of investigating the key technological components, architectures, algorithms and protocols is proposed, that facilitate highly reliable and autonomous BVLOS operations, aiming to enhance the alignment between market and operational needs and to better identify integration requirements between the different capabilities to be developed.