PVO:Panoramic Visual Odometry

Accurate visual odometry is essential for many fields such as robot navigation and autonomous driving .In this paper, we propose a novel panoramic visual odometry algorithm that is real-time, precise and robust .The main contributions of our work are a series of innovations that address the challenge of effective initialization and robust feature tracking based on panoramic camera. Wide field of view (FOV) is very important for robotic perception. Our algorithm takes advantage of the 360° FOV of a panoramic camera, which results in high accuracy of camera pose estimation and feature tracking stability. We use panoramic images directly without converting them to pinhole images. Through GPU acceleration, our implementation runs at an average 30 frames per second on a consumer laptop. In addition, we have done both indoor and outdoor experiments to validate proposed algorithm, the results show that ... we call our approach PVO (panoramic visual odometry).