Elmore Center for Uncrewed Aircraft Systems (ECUAS)


This center will provide a tiered approach to create and evaluate commercially viable UAS technologies. The first tier uses simulation to evaluate control algorithms and artificial intelligence for situational understanding. The second tier builds miniature cities and conducts experiments in natural and controlled environments. The third tier uses augmented reality to create realistic scenarios and test the responses. UAS are a driver of many engineering research topics and has great potential to change many industries. Due to safety regulations, most universities have to conduct experiments in confined space or rely on simulations. Unfortunately, neither approach can provide sufficient details to ensure a successful transition to realistic flights. Purdue has significant advantages over other universities due to several factors:

  1. West Lafayette already has many industry leaders conducting research related to aerospace technologies, including Maurice J. Zucrow Laboratories, Saab, and Rolls Royce. This UAS center would enable further collaborations and attract new organizations. An industrial consortium will be established.
  2. The proposed center is transformative because Purdue has a large base of faculty expertise that covers all of the relevant disciplines to create a vertically integrated Autonomous Uncrewed Aerial Systems (AUAS) center, from fundamental technologies to applications, including an efficient technology transfer process and a vibrant entrepreneurship ecosystem.
  3. The center will organize international competitions and invite leaders (from both academia and industry) to demonstrate their UAS technologies in realistic settings in West Lafayette.
  4. Multiple student clubs will receive UAS for creating innovative businesses. Purdue is one of the leading institutions of the Great Lakes Innovation Corps. This $15M grant aims to transfer technologies from research laboratories into the marketplace.




  • Yung-Hsiang Lu
    Computer Systems
    Professor of Electrical and Computer Engineering
  • Shreyas Sundaram
    Marie Gordon Associate Professor of Electrical and Computer Engineering

Core Team

  • Mary Comer
    Video Analytics
    Associate Professor of Electrical and Computer Engineering
  • Jing Gao
    Data Mining
    Associate Professor of Electrical and Computer Engineering
  • Mahsa Ghasemi
    Human Interaction
    Assistant Professor of Electrical and Computer Engineering
  • Jianghai Hu
    Distributed Systems
    Professor of Electrical and Computer Engineering
  • C.S. George Lee
    Professor of Electrical and Computer Engineering
  • Philip E. Paré
    Network Systems
    Assistant Professor of Electrical and Computer Engineering
  • Xiaoqian Joy Wang
    Explainable A.I.
    Assistant Professor of Electrical and Computer Engineering
  • Carla Zoltowski
    Undergraduate Research
    Assistant Professor of Engineering Practice

Purdue Collaborators

  • David Broecker
    Chief Innovation and Collaboration Officer, Purdue Research Foundation
  • Sabine Brunswicker
    Professor for Digital Innovation
  • David Cappelleri
    UAS Design
    Professor of Mechanical Engineering
  • James Goppert
    UAS Modeling
    Lecturer, Aeronautics and Astronautics
  • Troy Hege
    Vice President of Innovation and Technology, Purdue Research Foundation
  • Joseph Hupy
    Associate Professor, Aviation and Transportation Technology
  • Inseok Hwang
    Professor of Aeronautics and Astronautics
  • Damon Lercel
    Assistant Professor of Aviation and Transportation Technology
  • John Mott
    Transportation Systems
    Professor and Head, Aviation and Transportation Technology
  • Shaoshuai Mou
    Intelligent Systems and Mobile Agents
    Associate Professor of Aeronautics and Astronautics
  • Mo Shakouri
    Innovation Partners Institute Fellow, Purdue Research Foundation
  • Dengfeng Sun
    Professor of Aeronautics and Astronautics
  • Wei Zakharov
    Data Management and Dissemination
    Associate Professor of Libraries and School of Information Studies

Outside Collaborators

  • Md Tanvir Arafin
    Assistant Professor, George Mason University
  • Vipin Chaudhary
    Kevin J. Kranzusch Professor and Chair, Case Western Reserve University
  • Florence Chee
    Associate Professor, Loyola University
  • Yiran Chen
    Professor, Duke University
  • Trevor Darrell
    Professor in Residence, UC Berkeley
  • Kristen Grauman
    Professor, University of Texas
  • Kevin Kornegay
    Professor, Morgan State University
  • Michel Kornegay
    Associate Professor, Morgan State University
  • Renato Mancuso
    Assistant Professor, Boston University
  • Daniel Moreira
    Assistant Professor, Loyola University
  • Bryan Plummer
    Assistant Professor, Boston University
  • Kate Saenko
    Associate Professor, Boston University
  • George Thiruvathukal
    Professor, Loyola University
  • Zhao Zhang
    Research Associate, University of Texas


This center will enable fundamental research that creates breakthrough solutions for safe, trustable, and economic Autonomous Uncrewed Aerial Systems (AUAS) for commercial applications.

Real-Time Computer Vision: AUAS can produce large amounts of sensor data (especially videos from cameras) that must be processed promptly so that control decisions can be made during flights. This project will create efficient computer vision using the following approaches: First, lightweight neural networks will be created to process the data. Second, computer vision will be integrated with prior knowledge about the environment (such as maps, buildings locations and heights, weather) to expedite decision making. For AUAS to fly in populated areas, human trust is critical. The third step develops explainable machine learning models tailored to the environments.

Hierarchical Neural Networks: A new architecture, called tree hierarchical neural networks, breaks deep networks into multiple shallower networks and clusters final outputs into groups. Such a new architecture allows explicit tradeoffs of confidence, accuracy, and latency. This project will investigate improvements of the architecture for real-time control and explainable artificial intelligence.

Control, Planning, Navigation, and Coordination of UAS Fleets: Many applications require teams of UAS. Individual UAS may exchange sensor data and share information about the environment (such as obstacles), collectively, and autonomously make strategic decisions in order to complete the team's missions. Coordination may reduce the time needed for individual UAS in making decisions. This UAS center will develop real-time, scalable algorithms for collaborative control, planning, and navigation of UAS with guaranteed performance and reliability.

Situational Awareness and Understanding: UAS collect and analyze data in order to understand the environment, such as other moving objects and obstacles. UAS may also need to understand situations, such as severe weather or disasters. This center will develop algorithms for monitoring and understanding the changing environment, ensuring that the dynamics can be learned from the available measurements. These algorithms will be dependent on, and the guarantees will be a function of, the magnitude of the region of interest, the size of the UAS swarm, the quality of the measurements, the risk assessment of the area, and the nature of the phenomena of interest. This work will play a vital part in assuring that UAS can be used to build a better and safer world.

Resilience and Cybersecurity: For UAS to become truly pervasive, resilience and safety must be ensured. In a team of multiple UAS, compromising even a single UAS can have severe consequences. This UAS center will create secure UAS platforms and develop algorithms as well as protocols for cybersecurity. The solutions will be organized along several layers of protection. The lower layers are composed of control-theoretic cyber-security mechanisms to protect individual UAS against attacks and failures. The higher layers provide secure and resilient coordination algorithms for multiple UAS to dynamically reorganize for accomplishing the missions.

Human-Machine Interaction: AUAS serves human's needs. Thus, it is important to understand how UAS interacts with humans. This project will provide user interfaces to visualize and explain the processes of the decisions made by the AUAS. The interfaces integrate the sensor data (including video captured by the cameras on UAS), the timelines of the control decisions, communication among the team of UAS, and the internal states of the control software. The details can explain how UAS makes decisions, when the decisions are made, and the relationships among collaborating UAS. The interfaces will play key roles for the general public to trust UAS in everyday life as well as critical missions, such as emergency responses.

International Competitions: This center aims to become a world leader in AUAS research, innovation, and commercialization. The unique facilities created by this center will be used to organize international competitions to conduct a wide range of activities, including delivery, inspection of buildings, counting vehicles, etc. These competitions will raise the visibility of this center and establish Purdue as the world lead in AUAS.


Purdue Elmore Center for UAS (Uncrewed Aerial Systems). 2023/03/09 Speech by Goppert and Lercel

  1. James Goppert, Managing Director, Purdue UAS Research and Test Facility. Title: The Purdue UAS Research and Test Facility (PURT), A world-class facility for Autonomy Research and Education.
  2. Damon Lercel, Assistant Professor, Purdue Aviation and Transportation Technology. Title: Establishing an Unmanned Traffic Management System at Purdue.

Elmore ECE Emerging Frontiers Center

The Elmore Family School of Electrical and Computer Engineering created the Elmore ECE Emerging Frontiers Centers initiative to encourage, enable and sustain collaborations among ECE faculty, and others across campus, in emerging research areas that will significantly advance the frontiers of knowledge and have transformative impact on society.