Distributed Control and Vision-Based Estimation for UAS Autonomy
Abstract
This research will address the problem of coordinating multiple unmanned aircraft systems (UAS) to autonomously achieve and maintain a desired formation using vision to estimate relative position between UASes and estimate their motion in the environment. There are two primary research objectives. The first objective is to make formation control more robust to loss or jamming of global measurements or information (e.g., GPS signal and connection to the command center) and require no communication between UASes. This will be achieved by developing distributed controllers that need only inter-vehicle relative position measurements and that work under dynamic sensing topology. Stability of the formation will be rigorously established using theories of control and dynamic systems. The second objective is to use novel image-based pose estimation technique to enable UASes to estimate the relative position of their neighbors using only the passive vision sensor measurements. With the ability to achieve the desired formation in radio silence, the communication channel is free for other purposes, and UASes can increase their stealth. When other sensors such as GPS, IMU, etc. are available, motion estimated from the vision data can be fused with these measurements to attenuate the noise and improve the localization accuracy and make the agents robust to intermittent loss and interruption in sensor measurements.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 28, 2017
- Source ID
- FA86511710001
Entities
People
- Nicholas Gans
Organizations
- Air Force Research Laboratory
- United States Air Force
- University of Texas at Dallas