Dense visual-inertial odometry for tracking of aggressive motions

• Published in: 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO) pp. 576 - 583
• Main Authors: Yonggen Ling, Shaojie Shen
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2015
• Subjects: Cameras; Measurement uncertainty; Optimization; Reliability; Robot sensing systems; Tracking; Visualization

We propose a sliding window-based dense visual-inertial fusion method for real-time tracking of challenging aggressive motions. Our method combines recent advances in direct dense visual odometry, inertial measurement unit (IMU) preintegration, and graph-based optimization. At the front-end, direct...