Solar-Powered Long-Endurance UAV
for Real-Time Onboard Data Processing

Project Description


Given the wide range of possibilities, unmanned aerial vehicles (UAVs) represent a growing market in CPS and they are perceived as an "enabling technology" to re-consider the human involvement in many applications on a global scale. One of the major challenges in enabling this growth is UAV endurance. This is directly related to the amount of energy available to the UAV to perform its mission. This proposal looks to increase UAV endurance by trading off UAV performance with energy efficient computing. This requires mapping of mission and goals into energy needs and computational requirements. The goal of the project is to show that this trade can enable long-duration flight especially when solar energy is utilized as a primary energy source. The ambitious plan is to develop a light weight and efficient aircraft capable of maneuver-aware power adaptation and real-time video/sensor acquisition and processing for up to 12 hours of continuous flight (this limit being set by daylight hours). This project aims to expanding the theoretical and practical foundations for the design and integration of UAVs capable of real-time sensing and processing from an array of visual, acoustic and other sensors.

Power Modeling

Creating an accurate Power Model of aircraft power consumption is essential for strategic long-endurance flight.

uavAP
Modular Autopilot

The Modular Autopilot Framework, which is available as open-source (link below), allows several participants to work together by seamlessly switching between autopilot functionality.

Aircraft Optimization

Optimizing aircraft is crutial to extend the endurance of aircraft.

Future Work

Further improving the Power Model and incorporating it into an optimal planning algorithm will lead the way to long-endurance solar flight.

NSF Year 1 Poster & Presentation

Learn more about our first year's progress!

Publications


O. Dantsker, M. Theile, M. Caccamo, R. Mancuso, "Design, Development, and Initial Testing of a Computationally-Intensive, Long-Endurance Solar-Powered Unmanned Aircraft"
in AIAA Aviation and Aeronautics Forum and Exposition, Atlanta, GA, USA, June, 2018. pdf

O. Dantsker, M. Vahora, S. Imtiaz, M. Caccamo "High Fidelity Moment of Inertia Testing of Unmanned Aircraft"
in AIAA Aviation and Aeronautics Forum and Exposition, Atlanta, GA, USA, June, 2018. pdf

O. Dantsker, M. Theile, M. Caccamo, "A High-Fidelity, Low-Order Propulsion Power Model for Fixed-Wing Electric Unmanned Aircraft"
in AIAA/IEEE Electric Aircraft Technologies Symposium, Cincinnati, OH, USA, July, 2018. pdf

M. Theile, O. Dantsker, R. Nai, M. Caccamo, "uavEE: A Modular, Power-Aware Emulation Environment for Rapid Prototyping and Testing of UAV"
in IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), Hakodate, Japan, August, 2018. pdf

ICCPS 2018 Tutorial

Downloads

Contributors



Marco Caccamo

Marco is a Professor of Computer Science at the University of Illinois at Urbana-Champaign. He also has courtesy appointments in the Coordinated Science Lab (CSL) and the Department of Aerospace Engineering at the University of Illinois. He has chaired Real-Time Systems Symposium and Real-Time and Embedded Technology and Applications Symposium and served as General Chair of Cyber Physical Systems Week. He is an IEEE fellow and recipient of the Humboldt Professorship.

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Or Dantsker

Or is a PhD student in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign. His research interests include experimental aerodynamics and system integration of unmanned aircraft, particularly focusing on long-endurance solar flight. Or is also the co-founder of Al Volo LLC, which produces data acquisition systems for unmanned aircraft as well as other applications.



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Mirco Theile

Mirco is a Masters student in the Department of Electrical and Computer Engineering at the Technical University of Munich. In the scope of international education and research, he is a research scholar at the University of Illinois at Urbana-Champaign working on a power-aware autopilot for a long-endurance solar UAV.






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Ned Ellis

Ned Ellis is a sophomore undergraduate studying Electrical Engineering at UIUC. He is interested in integrating ML/AI techniques with Control Theory to enable smart air and space borne platforms. He also enjoys RTOS development for embedded systems and their use in reaching these goals.

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Richard Nai

Richard is an undergraduate student studying Computer Engineering at the University of Illinois at Urbana-Champaign.





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Arjun​ ​Nijhawan

Arjun​ is an undergraduate student studying Computer Engineering at the University of Illinois at Urbana-Champaign.





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Junda "Simon" Yu

Simon is an undergraduate student in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. He is currently working on the autopilot framework for the helicopter, including designing and tuning PID controllers, local planner algorithms, and other components for controlling the helicopter.

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Andrew Louis

Andrew is an Embedded Software Engineer at Bell Helicopters. He graduated in 2017 with a M.S. in Computer Science from the University of Illinois at Urbana-Champaign.





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Renato Mancuso

Renato is an Assistant Professor at Boston University. He graduated in 2017 with a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign.





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Daniel Amir

Daniel is an undergraduate student studying Computer Science and Engineering Physics at the University of Illinois at Urbana-Champaign.

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Raimi Shah

Raimi is an undergraduate student studying Computer Engineering at the University of Illinois at Urbana-Champaign.


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Jack Yang

Jack is an undergraduate student studying Computer Engineering at the University of Illinois at Urbana-Champaign.


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