Your expertise matters. Help us build our unique research infrastructure as lead user with 6 months free access!
The AIrTonomy team at Purdue University is implementing research infrastructure for autonomous aerial vehicles (AAVs) focusing on safe and trustworthy artificial intelligence and machine learning deployed in challenging environments. Please watch this AIrTonomy Overview video or read the info slides that explain what AIrTonomy provides to scholars and researchers in the field of AI/ML, control, human-autonomy teaming, and environmental sensing.
We are looking for scholars that are willing to be lead users of our NSF funded mid-scale infrastructure dedicated to bring R&D communities together on air autonomy. We define lead user as an individual that will have the interest and ability to access the new innovation, AIrTonomy before broad release to the general body of researchers. In typical design contexts, lead users give feedback to a designer leading to a better product that the lead user and others could eventually adopt.
What broad research communities are we inviting as lead users?
- AI/ML scholars focused on autonomous aerial vehicles
- Digital twin researchers
- Human-autonomy teaming researchers
What broader problem areas will the research infrastructure support?
- Complex missions of AAVs in real-world environments: BVLOS, long missions, high payload, weather disturbance, firefighting, first responders, urban airspace integration
- AAV operations in GPS-denied environments: Urban operations, search and rescue in buildings, transition from outdoor to indoor, flight in forests, counter UAS in urban canyons
- Human-autonomy-teaming (human-in-the-loop): Remote pilots (e.g. operations center), end-user interaction, brain-computer-interfaces (BCI), etc.
- Sensing/measuring with UAVs at different scales: Geometry models digital forestry, biomass measurement, etc.
What methodological and topical areas do we look for?
Topics for use case ideas (but not restricted to):
- AI/ML-driven UAV Perception and Object Detection/Tracking
- AI/ML-driven UAV Localization and Navigation
- AI/ML-driven Decision Making in UAV Operations and Human-Autonomy Teaming
- AI/ML-driven UAV Trajectory and Motion Planning
- AI/ML-driven UAV Control
- AI/ML-driven Swarm Coordination for UAVs
- AI/ML-assisted Environmental Monitoring with UAVs (e.g. Forestry, Wildfires)
- AI/ML-assisted Counterintelligence and Cybersecurity
- AI/ML-assisted Urban Airspace Management
AI/ML focus areas:
- Physics inspired neural networks (PINNs)
- Generative AI for data augmentation
- Federated learning
- Artificial General Intelligence (AGL)
- Reinforcement learning
- Model-based control
- Computer vision
- Edge computing
- Formal methods
- Safety in non-linear control theory (e.g. control barrier functions)
- Large Language Models (LLMs)
- Explainability and interpretability of AI/ML
- Digital twins and fidelity simulations
- Active SLAM
- Embodied AI
How can I share my research requirements?
We kindly ask you to share more details about your requirements related to our key components of the Purdue Unmanned aerial Proving Ground (PUP), the key physical infrastructure of AIrTonomy (see the video and slides here). Geographically organized within a triangle near Purdue University, it brings together unique indoor and outdoor facilities and infrastructure components that ensure that research can move back and forth from “lab to life”. We kindly ask you to assess the importance of each of the key components of the PUP, and also articulate your particular use and requirements when performing research with AIrTonomy.
To submit your ideas, please use the following submission form, addressing all components listed below in the form of a template/survey.
#1: A short pitch (300 words): This is the pitch of your idea submitted via the form of a short abstract. Please include following in your submission
- Problem statement/research question
- Proposed method and usage of AIrTonomy
- Expected outcome
- Scientific contribution
#2: An extended abstract plus interactive material (e.g. slides, videos, audio files, animations, etc.): This extended abstract submitted in the form of a .PDF should provide more detailed information about your study and how you envision to use AIrTonomy. We encourage you to use UML language (use cases), visualizations, or other means to illustrate your research idea in an easy-to-grasp way. You can also attach slides, and short videos if you wish to do so. Citations are not required but encouraged. We have developed a template for your document and slides here.
#3: Complementary info: During the submission process you will be asked to answer a few questions related to each of our components. It will help us to better understand your needs and how we need to adjust.
Awards and recognition
Lead user role and 6-months free access to research infrastructure!
A submission of a research plan will also allow you to become part of a lead user task force, who has 6 months free access to our infrastructure. The terms and conditions for such usage will be discussed at the workshop. Access can be granted as early as fall 2024, depending on your infrastructure needs. During that time you will have the opportunity to work with the AIrTonomy team to further shape the infrastructure development, and help with the implementation of some of the new components. We look forward to your ideas!
