Active-Vision Control Systems for Complex Adversarial 3-D Environments
Abstract
This project has included development of methods that utilize 2-D and 3-D imagery (e.g., from visual, FLIR, LADAR, acoustic) to enable aerial vehicles to autonomously detect and prosecute targets in uncertain complex 3-D adversarial environments, including capabilities and approaches inspired by those found in nature, and without relying upon highly accurate 3-D models of the environment. The new capabilities of autonomous sensing and control enable UAV/munition operations: in a clandestine/covert manner; in close proximity to hazards, structures, and/or terrain; and in uncertain/adversarial 3-D environments. Furthermore, the team performed a productive flying testbed activity as part of the program. This ensures that the methods are sound in the sense that they are: (l) implementable in real-time, (2) capable of practical use in the field, and (3) based on realistic/achievable sensor capabilities. This project is a Multidisciplinary University Research Initiative (MURI).
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 2009
- Accession Number
- ADA532870
Entities
People
- Allen R. Tannenbaum
- Anthony J. Calise
- Anthony J. Yezzi Jr.
- Eric N. Johnson
- Geogre Barbastathis
- Naira Hovakimyan
- Stafano Soatto
Organizations
- Georgia Tech