GateNet: An Efficient Deep Neural Network Architecture for Gate Perception Using Fish-Eye Camera in Autonomous Drone Racing
Huy Xuan Pham,Ilker Bozcan,Andriy Sarabakha,Sami Haddadin,Erdal Kayacan,Huy Xuan Pham,Ilker Bozcan,Andriy Sarabakha,Sami Haddadin,Erdal Kayacan
Fast and robust gate perception is of great importance in autonomous drone racing. We propose a convolutional neural network-based gate detector (GateNet1) that concurrently detects gate’s center, distance, and orientation with respect to the drone using only images from a single fish-eye RGB camera. GateNet achieves a high inference rate (up to 60 Hz) on an onboard processor (Jetson TX2). Moreove...
