VLocNet++: Deep Multitask Learning for Semantic Visual Localization and Odometry

• Published in: IEEE robotics and automation letters Vol. 3; no. 4; pp. 4407 - 4414
• Main Authors: Radwan, Noha, Valada, Abhinav, Burgard, Wolfram
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Autonomy; Datasets; Deep learning in robotics and automation; Image segmentation; Localization; Machine learning; Motion segmentation; Odometers; Scene analysis; Segmentation; Semantics; State estimation; Streaming media; Task analysis; visual learning; Visualization

Semantic understanding and localization are fundamental enablers of robot autonomy that have been tackled as disjoint problems for the most part. While deep learning has enabled recent breakthroughs across a wide spectrum of scene understanding tasks, its applicability to state estimation tasks has...