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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. Work in Progress: Interactive Introductory Online Modules on Wireless Communications and Radio-frequency Spectrum Sharing

   Dietrich, C. B. ; Polys, N. F. ; Reid, K. ; García Sheridan, J. A. ; Emenonye, D. ; Gomez, X. ; Tolley, J. ; Makin, C. ; Gaeddert, J. ( July 2021 , ASEE Annual Conference proceedings)

   1. Description of the objectives and motivation for the contribution to ECE education The demand for wireless data transmission capacity is increasing rapidly and this growth is expected to continue due to ongoing prevalence of cellular phones and new and emerging bandwidth-intensive applications that encompass high-definition video, unmanned aerial systems (UAS), intelligent transportation systems (ITS) including autonomous vehicles, and others. Meanwhile, vital military and public safety applications also depend on access to the radio frequency spectrum. To meet these demands, the US federal government is beginning to move from the proven but inefficient model of exclusive frequency assignments to a more-efficient, shared-spectrum approach in some bands of the radio frequency spectrum. A STEM workforce that understands the radio frequency spectrum and applications that use the spectrum is needed to further increase spectrum efficiency and cost-effectiveness of wireless systems over the next several decades to meet anticipated and unanticipated increases in wireless data capacity. 2. Relevant background including literature search examples if appropriate CISCO Systems’ annual survey indicates continued strong growth in demand for wireless data capacity. Meanwhile, undergraduate electrical and computer engineering courses in communication systems, electromagnetics, and networks tend to emphasize mathematical and theoretical fundamentals and higher-layer protocols, with less focus on fundamental concepts that are more specific to radio frequency wireless systems, including the physical and media access control layers of wireless communication systems and networks. An efficient way is needed to introduce basic RF system and spectrum concepts to undergraduate engineering students in courses such as those mentioned above who are unable to, or had not planned to take a full course in radio frequency / microwave engineering or wireless systems and networks. We have developed a series of interactive online modules that introduce concepts fundamental to wireless communications, the radio frequency spectrum, and spectrum sharing, and seek to present these concepts in context. The modules include interactive, JavaScript-based simulation exercises intended to reinforce the concepts that are presented in the modules through narrated slide presentations, text, and external links. Additional modules in development will introduce advanced undergraduate and graduate students and STEM professionals to configuration and programming of adaptive frequency-agile radios and spectrum management systems that can operate efficiently in congested radio frequency environments. Simulation exercises developed for the advanced modules allow both manual and automatic control of simulated radio links in timed, game-like simulations, and some exercises will enable students to select from among multiple pre-coded controller strategies and optionally edit the code before running the timed simulation. Additionally, we have developed infrastructure for running remote laboratory experiments that can also be embedded within the online modules, including a web-based user interface, an experiment management framework, and software defined radio (SDR) application software that runs in a wireless testbed initially developed for research. Although these experiments rely on limited hardware resources and introduce additional logistical considerations, they provide additional realism that may further challenge and motivate students. 3. Description of any assessment methods used to evaluate the effectiveness of the contribution, Each set of modules is preceded and followed by a survey. Each individual module is preceded by a quiz and followed by another quiz, with pre- and post-quiz questions drawn from the same pool. The pre-surveys allow students to opt in or out of having their survey and quiz results used anonymously in research. 4. Statement of results. The initial modules have been and are being used by three groups of students: (1) students in an undergraduate Introduction to Communication Systems course; (2) an interdisciplinary group of engineering students, including computer science students, who are participating in related undergraduate research project; and (3) students in a graduate-level communications course that includes both electrical and computer engineers. Analysis of results from the first group of students showed statistically significant increases from pre-quiz to post-quiz for each of four modules on fundamental wireless communication concepts. Results for the other students have not yet been analyzed, but also appear to show substantial pre-quiz to post-quiz increases in mean scores. 

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3. UNDERSTANDING SPEAKER ROLES ON A NATURALISTIC CORPUS: FEARLESS STEPS APOLLO 11

   Chandra-Shekar, M.M. ; Hansen, J.H.L. ( February 2023 , NASA Human Research Program Investigators Conference)

   INTRODUCTION: Apollo-11 (A-11) was the first manned space mission to successfully bring astronauts to the moon and return them safely. Effective team based communications is required for mission specialists to work collaboratively to learn, engage, and solve complex problems. As part of NASA’s goal in assessing team and mission success, all vital speech communications between these personnel were recorded using the multi-track SoundScriber system onto analog tapes, preserving their contribution in the success of one of the greatest achievements in human history. More than +400 personnel served as mission specialists/support who communicated across 30 audio loops, resulting in +9k hours of data for A-11. To ensure success of this mission, it was necessary for teams to communicate, learn, and address problems in a timely manner. Previous research has found that compatibility of individual personalities within teams is important for effective team collaboration of those individuals. Hence, it is essential to identify each speaker’s role during an Apollo mission and analyze group communications for knowledge exchange and problem solving to achieve a common goal. Assessing and analyzing speaker roles during the mission can allow for exploring engagement analysis for multi-party speaker situations. METHOD: The UTDallas Fearless steps Apollo data is comprised of 19,000 hours (A-11,A-13,A-1) possessing unique and multiple challenges as it is characterized by severe noise and degradation as well as overlap instances over the 30 channels. For our study, we have selected a subset of 100 hours manually transcribed by professional annotators for speaker labels. The 100 hours are obtained from three mission critical events: 1. Lift-Off (25 hours) 2. Lunar-Landing (50 hours) 3. Lunar-Walking (25 hours). Five channels of interest, out of 30 channels were selected with the most speech activity, the primary speakers operating these five channels are command/owners of these channels. For our analysis, we select five speaker roles: Flight Director (FD), Capsule Communicator (CAPCOM), Guidance, Navigation and, Control (GNC), Electrical, environmental, and consumables manager (EECOM), and Network (NTWK). To track and tag individual speakers across our Fearless Steps audio dataset, we use the concept of ‘where’s Waldo’ to identify all instances of our speakers-of-interest across a cluster of other speakers. Also, to understand speaker roles of our speaker-of-interests, we use speaker duration of primary speaker vs secondary speaker and speaker turns as our metrics to determine the role of the speaker and to understand their responsibility during the three critical phases of the mission. This enables a content linking capability as well as provide a pathway to analyzing group engagement, group dynamics of people working together in an enclosed space, psychological effects, and cognitive analysis in such individuals. IMPACT: NASA’s Apollo Program stands as one of the most significant contributions to humankind. This collection opens new research options for recognizing team communication, group dynamics, and human engagement/psychology for future deep space missions. Analyzing team communications to achieve such goals would allow for the formulation of educational and training technologies for assessment of STEM knowledge, task learning, and educational feedback. Also, identifying these personnel can help pay tribute and yield personal recognition to the hundreds of notable engineers and scientist who made this feat possible. ILLUSTRATION: In this work, we propose to illustrate how a pre-trained speech/language network can be used to obtain powerful speaker embeddings needed for speaker diarization. This framework is used to build these learned embeddings to label unique speakers over sustained audio streams. To train and test our system, we will make use of Fearless Steps Apollo corpus, allowing us to effectively leverage a limited label information resource (100 hours of labeled data out of +9000 hours). Furthermore, we use the concept of 'Finding Waldo' to identify key speakers of interest (SOI) throughout the Apollo-11 mission audio across multiple channel audio streams. 

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4. 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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5. FEARLESS STEPS: ADVANCEMENTS IN SPEECH TECHNOLOGY AND CORPUS DEVELOPMENT FOR NATURALISTIC AUDIO

   Joglekar, A. ; Hansen, J.H.L. ; Yousefi, M. ; Chandra Shekar, M. ; Chen, S.-J. ; Belitz, C. ( February 2023 , NASA Human Research Program Investigators Conference)

   INTRODUCTION: CRSS-UTDallas initiated and oversaw the efforts to recover APOLLO mission communications by re-engineering the NASA SoundScriber playback system, and digitizing 30-channel analog audio tapes – with the entire Apollo-11, Apollo-13, and Gemini-8 missions during 2011-17 [1,6]. This vast data resource was made publicly available along with supplemental speech & language technologies meta-data based on CRSS pipeline diarization transcripts and conversational speaker time-stamps for Apollo team at NASA Mission Control Center, [2,4]. In 2021, renewed efforts over the past year have resulted in the digitization of an additional +50,000hrs of audio from Apollo 7,8,9,10,12 missions, and remaining A-13 tapes. Cumulative digitization efforts have enabled the development of the largest publicly available speech data resource with unprompted, real conversations recorded in naturalistic environments. Deployment of this massive corpus has inspired multiple collaborative initiatives such as Web resources ExploreApollo (https://app.exploreapollo.org) LanguageARC (https://languagearc.com/projects/21) [3]. ExploreApollo.org serves as the visualization and play-back tool, and LanguageARC the crowd source subject content tagging resource developed by UG/Grad. Students, intended as an educational resource for k-12 students, and STEM/Apollo enthusiasts. Significant algorithmic advancements have included advanced deep learning models that are now able to improve automatic transcript generation quality, and even extract high level knowledge such as ID labels of topics being spoken across different mission stages. Efficient transcript generation and topic extraction tools for this naturalistic audio have wide applications including content archival and retrieval, speaker indexing, education, group dynamics and team cohesion analysis. Some of these applications have been deployed in our online portals to provide a more immersive experience for students and researchers. Continued worldwide outreach in the form of the Fearless Steps Challenges has proven successful with the most recent Phase-4 of the Challenge series. This challenge has motivated research in low level tasks such as speaker diarization and high level tasks like topic identification. IMPACT: Distribution and visualization of the Apollo audio corpus through the above mentioned online portals and Fearless Steps Challenges have produced significant impact as a STEM education resource for K-12 students as well as a SLT development resource with real-world applications for research organizations globally. The speech technologies developed by CRSS-UTDallas using the Fearless Steps Apollo corpus have improved previous benchmarks on multiple tasks [1, 5]. The continued initiative will extend the current digitization efforts to include over 150,000 hours of audio recorded during all Apollo missions. ILLUSTRATION: We will demonstrate WebExploreApollo and LanguageARC online portals with newly digitized audio playback in addition to improved SLT baseline systems, the results from ASR and Topic Identification systems which will include research performed on the corpus conversational. Performance analysis visualizations will also be illustrated. We will also display results from the past challenges and their state-of-the-art system improvements. 

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