Autonomous systems operate in the air, on land, and even underwater. Sensing and avoiding objects is a critical necessity for autonomous vehicles when navigating their environment. Detecting objects in a vehicle's path and rapidly computing changes to the vehicle's trajectory requires object detection, path optimization, and vehicle guidance. Current solutions to this problem using optics can be limited to daylight applications, require significant system resources, and suffer in low-light or foul weather environments.
Autonomous systems operate in the air, on land, and even underwater. Sensing and avoiding objects is a critical necessity for autonomous vehicles when navigating their environment. Detecting objects in a vehicle's path and rapidly computing changes to the vehicle's trajectory requires object detection, path optimization, and vehicle guidance. Current solutions to this problem using optics can be limited to daylight applications, require significant system resources, and suffer in low-light or foul weather environments.
LLNL’s sense-and-avoid technology offers performance advantages over costlier imaging-based systems in:
- Signal to noise reduction
- Improved detection probabilities
- Reduced false alarm rates
- Lower computational cost and reduced processing requirements
- Lower sensor costs
- All-weather operational capability
- Ability to train the system even though the “scene” is not an image.
LLNL’s autonomous sense and avoid system can be used for autonomous and semi-autonomous vehicle applications involving unmanned air vehicles (UAV's), unmanned ground vehicles (UGV's), and unmanned underwater vehicles (UUV's).
LLNL has two issued U.S. patents, eight U.S. patents pending and patent applications in six foreign countries on its low-cost autonomous sense and avoid technology.