Intelligent fly-by-feel systems for autonomous aircraft
Award last edited on: 6/21/2021

Sponsored Program
Awarding Agency
Total Award Amount
Award Phase
Solicitation Topic Code
Principal Investigator
Amrita Kumar

Company Information

Acellent Technologies Inc

835 Stewart Drive
Sunnyvale, CA 94085
   (408) 745-1188

Research Institution

Ohio State University

Phase I

Contract Number: FA8649-21-P-0163
Start Date: 11/19/2020    Completed: 5/19/2021
Phase I year
Phase I Amount
Future intelligent autonomous vehicles like the Orb/eVTOL/UAM (Electric Vertical Takeoff and Landing/Urban Air Mobility) vehicles need the ability to “feel”, “think”, and “react” in real time to enable state-sensing, awareness, and self-diagnostic capabilities in complex dynamic environments to ensure safe operations, reduced maintenance costs, and complete life-cycle management. The proposed STTR will focus on the development and transition of bio-inspired stretchable sensor technologies integrated with composite air vehicle structures to provide the ability for state sensing as well as operational and flight changes to enable Fly-by-Feel sensing capability mimicking the biological bird flight. The team of Acellent (lead) and Stanford University supported by Boeing and Triumph Aerospace will collaboratively work on this program. In Phase I, the team will develop micro-fabricated stretchable sensor networks, including integrated piezoelectric, strain, and temperature sensors that are designed and monolithically embedded in a composite aircraft structure. In addition, artificial deep learning algorithms integrated with physics-driven models will be developed to interpret the sensing data collected in real time in terms of flight state and health condition of the vehicle. An experimental evaluation and assessment of the intelligent composite structure will be demonstrated through wind tunnel testing. Plans for testing the complete system in Phase II when integrated with an air vehicle identified in Phase I will also be developed.

Phase II

Contract Number: FA8649-21-P-1617
Start Date: 8/9/2021    Completed: 11/9/2022
Phase II year
Phase II Amount
Future intelligent autonomous vehicles like the Orb/eVTOL/UAM (Electric Vertical Takeoff and Landing/Urban Air Mobility) vehicles will be able to “feel”, “think”, and “react” in real time by incorporating high-resolution state-sensing, awareness, and self-diagnostic capabilities. They will be able to sense and observe phenomena at unprecedented length and time scales allowing for superior performance in complex dynamic environments, safer operation, reduced maintenance costs, and complete life-cycle management. Despite the importance of vehicle state sensing and awareness, however, the current state of the art is primitive as well as prohibitively heavy, expensive, and complex. Therefore, new Fly-by-Feel technologies are required for the next generation of intelligent aerospace structures that will utilize AI to sense the environmental conditions and structural state, and effectively interpret the sensing data to achieve real-time state awareness to employ appropriate self-diagnostics under varying operational environments. Acellent is teaming with Stanford University, USAF and The Boeing Company in this STTR project to develop a Fly-by-Feel (FBF) autonomous system to significantly enhance agility of drones by integrating directly on the wings a nerve-like stretchable multimodal sensor network with AI-based state sensing and health diagnostic software to mimic the biological sensory systems like birds. Once integrated with the wings, the distributed sensor data will be collected and processed in real-time through AI-based diagnostics for flight-state estimation in terms of lift, drag, flutter, angle of attack, and damage/failure of the component in real time so that the system can interface with the controller to significantly enhance the maneuverability and survivability of the vehicle. Phase 1 focused on manufacturing, integrating and testing the network in the laboratory environment. Phase 2 program will mature the technology to TRL 5-6 via integration with a UAV to flight test the complete UAV in a flight regime using a wind tunnel.