REU Site: Undergraduate Research Opportunities in Unmanned Systems Foundations and Applications

Unmanned Systems

For information contact

Justin Bradley

Assistant Professor, School of Computing

Dung Hoang Tran

Assistant Professor, School of Computing

Funding Source

NSF CNS-2244116

See Projects

Unmanned Systems scholars at the end-of-the-year banquet.
Unmanned Systems scholars at the end-of-the-year banquet.

Who should apply


Related fields

  • Robotics
  • Cyber-Physical Systems
  • Human-Robot Interaction
  • Formal Methods

Eligibility

Participation in the Nebraska Summer Research Program is limited to students who meet the following criteria:
  • U.S. Citizen or Permanent Resident
  • Current undergraduate with at least one semester of coursework remaining before obtaining a bachelor's degree

See Eligibility for more information.

How to apply

This program has an alternative application. Please visit https://etap.nsf.gov/award/2278/opportunity/5612 to apply.

Submit the standard UNL SRP app only if you wish to be considered for additional SRP programs.

About the Program

The REU site will provide undergraduates with a comprehensive research experience in the context of unmanned systems, a rapidly growing field of scientific and technological research. REU students will participate in carefully prepared research projects on unmanned systems with topics including unmanned aircraft system (UAS) vision-based control, behavior studies of robots in complex environments around humans, characterizing and developing vehicles for close environmental interaction, multi-agent unmanned aerial system design and control, and synergistic high resiliency communication. Research activities across the projects will be structured to provide a systematic research experience for the cohort, while enabling flexibility for each participant to focus on a particular area. The projects will be hosted at the University of Nebraska-Lincoln's Nebraska Intelligent MoBile Unmanned Systems Lab (UNL NIMBUS), which has mentored over 80 undergraduate students, and is a leader in aerial unmanned systems and their application to the environment.

Visit https://etap.nsf.gov/award/2278/opportunity/5612 to apply to this program.

Unmanned systems students working on swarming drones.
Unmanned systems students working on swarming drones.

Benefits

  • Competitive stipend: $7,000
  • Suite-style room and meal plan
  • Travel expenses to and from Lincoln
  • Campus parking and/or bus pass
  • Full access to the Campus Recreation Center and campus library system
  • Wireless internet access

Learn more about academic and financial benefits.

Events

  • Department seminars and presentations
  • Professional development workshops (e.g., applying to graduate school, taking the GRE)
  • Welcome picnic
  • Day trip to Omaha's Henry Doorly Zoo and Aquarium
  • Outdoor adventures
  • Research symposium

Mentors and Projects

Dr. Justin Bradley School of Computing

Multi-agent UAS Design, Control, and Applications

Unmanned, multi-agent systems can multiply the effectiveness of systems and significantly increase their individual capabilities through cooperation. However, multi-agent systems also present new challenges as failures can compound, and small inefficiencies are magnified. The NIMBUS lab has been developing an outdoor-based multiagent UAS testbed of 10-12 drones that can be used in a wide variety of multi-agent applications. The system is highly configurable, reliable, with an emphasis on enabling repeatability. Vehicles are identical, and Docker is used as a rapid deployment mechanism to ensure uniformity. 

Close interactions of UAS with the environment

Current UAS are able to collect large amounts of data for scientists by flying high and taking pictures. The next generation of drones will be able to do more by directly interacting with the environment. The NIMBUS Lab is leading a collaborative effort to develop the next generation of drone algorithms and systems to enable close interaction with a rain-forest environment. Rain-forest canopies are important ecosystems for diverse plant and animal life, however, validating the model-based predictions for scientific decisions about these environments is difficult due to a lack of efficient data collection methods. We are developing an UAS-based leaf cutting system that will allow scientists to collect leaf samples from the canopy without putting people at risk or disturbing sensitive portions of the environment. The system will be able to collect leaf samples from the top of the canopy and also from within the canopy while maintaining a safe distance between the tree and the UAS. 

Dr. Brittany Duncan School of Computing

Development of Proficiency with Robotic Systems across Users, Domains, and Applications

Achieving a goal of integrative, heterogeneous, multi-robot systems for environmental sensing and deployment by non-roboticists will require systems that can perceive and adapt to the user’s skill level and work collaboratively to help them achieve their goals. This project will seek to understand user proficiency across aerial, water surface, and underwater platforms used for monitoring beaver activity. The study of expertise and proficiency can help us understand the learning and knowledge acquisition processes to inform better instruction and training methods. 

Dr. Shuai Nie School of Computing

Synergistic Communications with High Resiliency

High-throughput wireless communications rely on available spectrum resources to provide wide bandwidth. Equipping the UAS with advanced communication capabilities will benefit data transfer between ground infrastructure and drones in many scenarios, ranging from fire and rescue to providing coverage for users not accessible with traditional cellular networks. Current fifth-generation (5G) networks adopt millimeter-wave (mmWave) spectrum as part of the key technology to enable multi-giga-bits-per-second (Gbps) end-to-end links. However, mmWave is known to have much higher free-space path loss as compared with its counterpart in the microwave frequency, thus necessitates the use of phased antenna arrays to generate beams with high gains and compensate for the path loss. As the agents in a UAS team move in the air, the dynamic position leads to the issue of beam misalignment, which needs constant corrections in antenna array patterns in a timely manner to maintain a stable link. 

Dr. Dung-Hoang Tran School of Computing

Vision-based Control for Collaborative Autonomous Robots

Many safety-critical applications, such as wildfire management, surveillance, and rescue in natural disasters, and nuclear power plant monitoring and maintenance, require the precise collaboration of heterogeneous multiple mobile robots operating under dangerous and intense conditions. In this context, precise control of air/ground robots under environmental uncertainties such as strong wind and GPS-based localization errors is critical to optimize their utilization and energy consumption while preserving their safety. The NIMBUS Lab has pioneered the use of UAS in fire monitoring and ignition, but UASs are not being leveraged to collaborate with ground vehicles for a wider range of applications.