Self-Supervised Drivable Area and Road Anomaly Segmentation Using RGB-D Data For Robotic Wheelchairs
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2019.2932874
Abstract: The segmentation of drivable areas and road anomalies are critical capabilities to achieve autonomous navigation for robotic wheelchairs. The recent progress of semantic segmentation using deep learning techniques has presented effective results. However, the acquisition… read more here.
Keywords: self supervised; robotic wheelchairs; road; segmentation ... See more keywords
Dynamic Fusion Module Evolves Drivable Area and Road Anomaly Detection: A Benchmark and Algorithms
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2021.3064089
Abstract: Joint detection of drivable areas and road anomalies is very important for mobile robots. Recently, many semantic segmentation approaches based on convolutional neural networks (CNNs) have been proposed for pixelwise drivable area and road anomaly… read more here.
Keywords: area road; fusion; road; benchmark ... See more keywords