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1. A Predictive Control Framework for UAS Trajectory Planning Considering 4G/5G Communication Link Quality

   https://doi.org/10.1109/ICNS58246.2023.10124315  

   Zuo, Rui ; Wang, Zixi ; Caicedo Bastidas, Carlos E. ; Cenk Gursoy, M. ; Solomon, Adrian ; Qiu, Qinru ( April 2023 , Integrated Communication, Navigation and Surveillance Conference (ICNS))

   A reliable command and control (C2) data link is required for unmanned aircraft systems (UAS) operations in order to monitor the status and support the control of UAS. A practical realization of the C2 communication and mission data links for commercial UAS operations is via LTE/5G networks. While the trajectory of each UAS directly determines the flight distance and mission cost in terms of energy dissipation, it also has a strong correlation to the quality of the communication link provided by a serving base station, where quality is defined as the achieved signal-to-interference-plus-noise ratio (SINR) required to maintain the control link of the UAS. Due to signal interference and the use of RF spectrum resources, the trajectory of a UAS not only determines the communication link quality it will encounter, but also influences the link quality of other UAS in its vicinity. Therefore, effective UAS traffic management must plan the trajectory for a group of UAS taking into account the impact to the interference levels of other base stations and UAS communication links. In this paper, an SINR Aware Predictive Planning (SAPP) framework is presented for trajectory planning of UAS leveraging 4G/5G communication networks in a simulated environment. The goal is to minimize flight distance while ensuring a minimum required link quality for C2 communications between UAS and base stations. The predictive control approach is proposed to address the challenges of the time varying SINR caused by the interference from other UAS’s communication. Experimental results show that the SAPP framework provides more than 3dB improvements on average for UAS communication parameters compared to traditional trajectory planning algorithms while still achieving shortest path trajectories and collision avoidance. 

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2. Simulating unmanned aerial vehicle swarms with the UB-ANC Emulator

   https://doi.org/10.1177/1756829319837668  

   Modares, Jalil ; Mastronarde, Nicholas ; Dantu, Karthik ( April 2019 , International Journal of Micro Air Vehicles)

   Recent advances in multi-rotor vehicle control and miniaturization of hardware, sensing, and battery technologies have enabled cheap, practical design of micro air vehicles for civilian and hobby applications. In parallel, several applications are being envisioned that bring together a swarm of multiple networked micro air vehicles to accomplish large tasks in coordination. However, it is still very challenging to deploy multiple micro air vehicles concurrently. To address this challenge, we have developed an open software/hardware platform called the University at Buffalo’s Airborne Networking and Communications Testbed (UB-ANC), and an associated emulation framework called the UB-ANC Emulator. In this paper, we present the UB-ANC Emulator, which combines multi-micro air vehicle planning and control with high-fidelity network simulation, enables practitioners to design micro air vehicle swarm applications in software and provides seamless transition to deployment on actual hardware. We demonstrate the UB-ANC Emulator’s accuracy against experimental data collected in two mission scenarios: a simple mission with three networked micro air vehicles and a sophisticated coverage path planning mission with a single micro air vehicle. To accurately reflect the performance of a micro air vehicle swarm where communication links are subject to interference and packet losses, and protocols at the data link, network, and transport layers affect network throughput, latency, and reliability, we integrate the open-source discrete-event network simulator ns-3 into the UB-ANC Emulator. We demonstrate through node-to-node and end-to-end measurements how the UB-ANC Emulator can be used to simulate multiple networked micro air vehicles with accurate modeling of mobility, control, wireless channel characteristics, and network protocols defined in ns-3.

    

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3. Learning-to-Fly: Learning-based Collision Avoidance for Scalable Urban Air Mobility

   https://doi.org/10.1109/ITSC45102.2020.9294425  

   Rodionova, Alena ; Pant, Yash Vardhan ; Jang, Kuk ; Abbas, Houssam ; Mangharam, Rahul ( January 2020 , IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC))

   null (Ed.)

   With increasing urban population, there is global interest in Urban Air Mobility (UAM), where hundreds of autonomous Unmanned Aircraft Systems (UAS) execute missions in the airspace above cities. Unlike traditional human-inthe-loop air traffic management, UAM requires decentralized autonomous approaches that scale for an order of magnitude higher aircraft densities and are applicable to urban settings. We present Learning-to-Fly (L2F), a decentralized on-demand airborne collision avoidance framework for multiple UAS that allows them to independently plan and safely execute missions with spatial, temporal and reactive objectives expressed using Signal Temporal Logic. We formulate the problem of predictively avoiding collisions between two UAS without violating mission objectives as a Mixed Integer Linear Program (MILP). This however is intractable to solve online. Instead, we develop L2F, a two-stage collision avoidance method that consists of: 1) a learning-based decision-making scheme and 2) a distributed, linear programming-based UAS control algorithm. Through extensive simulations, we show the real-time applicability of our method which is ≈6000× faster than the MILP approach and can resolve 100% of collisions when there is ample room to maneuver, and shows graceful degradation in performance otherwise. We also compare L2F to two other methods and demonstrate an implementation on quad-rotor robots. 

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4. SkyTrakx: A Toolkit for Simulation and Verification of Unmanned Air-Traffic Management Systems

   https://doi.org/10.1109/ITSC48978.2021.9564492  

   Hsieh, Chiao ; Sibai, Hussein ; Taylor, Hebron ; Ni, Yifeng ; Mitra, Sayan ( September 2021 , EEE International Intelligent Transportation Systems Conference (ITSC))

   The key concept for safe and efficient traffic management for Unmanned Aircraft Systems (UAS) is the notion of operation volume (OV). An OV is a 4-dimensional block of airspace and time, which can express an aircraft’s intent, and can be used for planning, de-confliction, and traffic management. While there are several high-level simulators for UAS Traffic Management (UTM), we are lacking a frame- work for creating, manipulating, and reasoning about OVs for heterogeneous air vehicles. In this paper, we address this and present SkyTrakx—a software toolkit for simulation and verification of UTM scenarios based on OVs. First, we illustrate a use case of SkyTrakx by presenting a specific air traffic coordination protocol. This protocol communicates OVs between participating aircraft and an airspace manager for traffic routing. We show how existing formal verification tools, Dafny and Dione, can assist in automatically checking key properties of the protocol. Second, we show how the OVs can be computed for heterogeneous air vehicles like quadcopters and fixed-wing aircraft using another verification technique, namely reachability analysis. Finally, we show that SkyTrakx can be used to simulate complex scenarios involving heterogeneous vehicles, for testing and performance evaluation in terms of workload and response delays analysis. Our experiments delineate the trade-off between performance and workload across different strategies for generating OVs. 

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5. 3GPP Mobile Telecommunications Technology on the Moon

   https://doi.org/10.1109/AERO55745.2023.10115746  

   Edwards, Bernard ; Wagner, Raymond ; Zemba, Michael ; Millard, Wesley ; Braham, Stephen ; Gifford, Kevin ; Somerlock, Oscar ( March 2023 , IEEE)

   Under NASA’s Artemis program, NASA is planning to send astronauts back to the Moon in the next couple of years. Near term missions will be analogous but much more sophisticated versions of the last couple of Apollo missions. However, unlike Apollo, this time NASA intends to put the infrastructure in place to support long term human presence and eventual industrialization of the Moon. To make this vision a reality, NASA plans to collaborate with commercial and international partners as much as possible as opposed to developing, building, and operating equipment on its own. Lunar infrastructure will eventually be built over time by many organizations, public and private, to support sustained human exploration, science, and industrial activities. Obviously, this vision for the future will be impossible without a robust lunar communications and navigation system that can support many users with varying degrees of services. On Earth, most people are very familiar with the 3rd Generation Partnership Project (3GPP) 5G mobile telecommunications technology. NASA’s Space Technology Mission Directorate and NASA’s Space Communications and Navigation office would like to see a lunar communications and navigation network with similar capabilities to the cellular communication networks most of us enjoy today. Building such a network will require participation by many organizations. This paper will provide an overview of NASA’s interest in using 5G and beyond on the lunar surface; it will also describe current work based on 3GPP standards within NASA or funded by NASA, such as Nokia’s upcoming Tipping Point demonstration of 4G / LTE on the lunar surface. 

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