Night Rider: Visual Odometry Using Headlights

Abstract

Visual Odometry (VO) is a key enabling technology for mobile robotic systems that provides a relative motion estimate from a sequence of camera images. Cameras are comparatively inexpensive sensors, and provide large amounts of useful data, making them one of the most common sensors in mobile robotics. However, because they are passive, they are dependent on external lighting, which can restrict their usefulness. Using headlights as an alternate lighting source, this paper investigates outdoor stereo VO performance under all lighting conditions during nearly 10 km of driving over 30 hours. Challenges include limited visibility range, a dynamic light source, intensity hotspots, and others. Another large issue comes from blooming and lens flare at dawn and dusk, when the camera is looking directly into the sun. In our experiments, nighttime driving with headlights has a moderately increased error of 2.38% over 250 m compared to the daytime error of 1.5%. To the best of our knowledge this is the first quantitative study of VO performance at night using headlights.