NVIDIA Corporation
INTERSECTION POSE DETECTION IN AUTONOMOUS MACHINE APPLICATIONS

Abstract:

In various examples, live perception from sensors of a vehicle may be leveraged to generate potential paths for the vehicle to navigate an intersection in real-time or near real-time. For example, a deep neural network (DNN) may be trained to compute various outputs--such as heat maps corresponding to key points associated with the intersection, vector fields corresponding to directionality, heading, and offsets with respect to lanes, intensity maps corresponding to widths of lanes, and/or classifications corresponding to line segments of the intersection. The outputs may be decoded and/or otherwise post-processed to reconstruct an intersection--or key points corresponding thereto--and to determine proposed or potential paths for navigating the vehicle through the intersection.