Applying Surface Normal Information in Drivable Area and Road Anomaly Detection for Ground Mobile Robots
Hengli Wang,Rui Fan,Yuxiang Sun,Ming Liu,Hengli Wang,Rui Fan,Yuxiang Sun,Ming Liu
The joint detection of drivable areas and road anomalies is a crucial task for ground mobile robots. In recent years, many impressive semantic segmentation networks, which can be used for pixel-level drivable area and road anomaly detection, have been developed. However, the detection accuracy still needs improvement. Therefore, we develop a novel module named the Normal Inference Module (NIM), wh...
