Publication:
Large-Scale Direct SLAM with Stereo Cameras, IROS 2015
Authors:
Jakob Engel,
Jörg Stückler,
Daniel Cremers
Paper:
http://vision.in.tum.de/stereo-lsdslam
Abstract:
We propose a novel Large-Scale Direct SLAM
algorithm for stereo cameras (Stereo LSD-SLAM) that runs
in real-time at high frame rate on standard CPUs. In contrast
to sparse interest-point based methods, our approach aligns
images directly based on the photoconsistency of all high-
contrast pixels, including corners, edges and high texture areas.
It concurrently estimates the depth at these pixels from two
types of stereo cues: Static stereo through the fixed-baseline
stereo camera setup as well as temporal multi-view stereo
exploiting the camera motion. By incorporating both disparity
sources, our algorithm can even estimate depth of pixels that
are under-constrained when only using fixed-baseline stereo.
Using a fixed baseline, on the other hand, avoids scale-drift
that typically occurs in pure monocular SLAM. We furthermore
propose a robust approach to enforce illumination invariance,
capable of handling aggressive brightness changes between
frames – greatly improving the performance in realistic settings.
In experiments, we demonstrate state-of-the-art results on
stereo SLAM benchmarks such as Kitti or challenging datasets
from the EuRoC Challenge 3 for micro aerial vehicles.
