Manager of Texas Instruments’ Perception & Analytics Laboratory
Heterogeneous sensor fusion for highly automated vehicles
As highly automated vehicles begin to emerge, they will be instrumented with multiple vision cameras, radar, LiDAR and ultrasonic sensors to support safety, driving and parking functions. When combined with efficient and distributed processing, these heterogeneous sensors can enable scalable perception systems for supporting SAE Level 3 capabilities and beyond. We explore heterogeneous sensor fusion to understand how they provide both the redundancy and the robustness needed to make sense of complex environments, even under challenging conditions.
About the Speaker
Darnell Moore is a Distinguished Member of Technical Staff and Manager of Texas Instruments’ Perception & Analytics Laboratory (PAL), which is at the intersection of silicon architecture and high-performance applications using vision, sensor fusion and environmental modeling. Darnell directs research and development for TI processors used in highly automated vehicles, unsupervised robots and pilotless drones. Darnell joined TI in 2000 after completing a master’s degree and doctorate from Georgia Tech and a bachelor’s degree from Northwestern University, all in electrical engineering. A native of Chattanooga, Tennessee, he is married with two children.