A maximum likelihood estimation calibration uses a radial laser scanner to correct depth camera errors, yielding more accurate 3D planar reconstructions and global measurements for mobile robots.
RGB-Depth SLAM Review
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
Simultaneous Localization and Mapping (SLAM) have made the real-time dense reconstruction possible increasing the prospects of navigation, tracking, and augmented reality problems. Some breakthroughs have been achieved in this regard during past few decades and more remarkable works are still going on. This paper presents an overview of SLAM approaches that have been developed till now. Kinect Fusion algorithm, its variants, and further developed approaches are discussed in detailed. The algorithms and approaches are compared for their effectiveness in tracking and mapping based on Root Mean Square error over online available datasets.
fields
cs.RO 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Intrinsic Calibration of Depth Cameras for Mobile Robots using a Radial Laser Scanner
A maximum likelihood estimation calibration uses a radial laser scanner to correct depth camera errors, yielding more accurate 3D planar reconstructions and global measurements for mobile robots.