Odometry
Related papers: 20
About
Odometry is the process of estimating a robot's position and orientation over time by integrating motion measurements from onboard sensors. The term originally referred to tracking wheel rotations on wheeled robots, but has expanded to encompass visual odometry (using cameras), lidar odometry (using laser scanners), and inertial odometry (using accelerometers and gyroscopes), as well as tightly fused combinations of these modalities. As a robot moves, each new sensor reading is used to compute an incremental motion estimate that is appended to a running pose trajectory, enabling the robot to track where it is without relying on external infrastructure like GPS. Odometry is a foundational component in autonomous navigation stacks, underpinning simultaneous localization and mapping (SLAM), path planning, and feedback control. It has been validated across diverse platforms — ground vehicles, aerial drones, and planetary rovers. Because all odometry methods accumulate small errors over time (known as drift), researchers develop correction strategies, loop-closure techniques, and sensor fusion pipelines to maintain accuracy over long distances and durations, making robust odometry critical to any autonomously operating robot.
Top Researchers
Top Institutes
Top Cited Papers
Are we ready for autonomous driving? The KITTI vision benchmark suite
Andreas Geiger, P Lenz, R. Urtasun
Citations: 14348 • 2012
VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator
Tong Qin, Peiliang Li, Shaojie Shen
Citations: 4390 • 2018
A benchmark for the evaluation of RGB-D SLAM systems
Jrgen Sturm, Nikolas Engelhard, Felix Endres, Wolfram Burgard, Daniel Cremers
Citations: 3918 • 2012
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
Tixiao Shan, Brendan Englot, Drew Meyers, Wei Wang, Carlo Ratti, Daniela Rus
Citations: 1955 • 2020
Keyframe-based visual–inertial odometry using nonlinear optimization
Stefan Leutenegger, Simon Lynen, Michael Bosse, Roland Siegwart, Paul Furgale
Citations: 1697 • 2014
Visual Odometry [Tutorial]
Davide Scaramuzza, Friedrich Fraundorfer
Citations: 1485 • 2011
Globally Consistent Range Scan Alignment for Environment Mapping
Feng Lu, Evangelos Milios
Citations: 1272 • 1997
StereoScan: Dense 3d reconstruction in real-time
Andreas Geiger, Julius Ziegler, Christoph Stiller
Citations: 1102 • 2011
Toward a Fully Autonomous UAV: Research Platform for Indoor and Outdoor Urban Search and Rescue
Teodor Tomić, Korbinian Schmid, Philipp Lutz, Andreas Dömel, Michael Kaßecker, Elmar Mair, Iris Grixa, Felix Ruess, Michael Suppa, Darius Burschka
Citations: 802 • 2012
Measurement and correction of systematic odometry errors in mobile robots
J. Borenstein, Liqiang Feng
Citations: 792 • 1996
Two years of Visual Odometry on the Mars Exploration Rovers
Mark Maimone, Yang Cheng, Larry Matthies
Citations: 642 • 2007
Visual Odometry and Mapping for Autonomous Flight Using an RGB-D Camera
Albert S. Huang, Abraham Bachrach, Peter Henry, Michael Krainin, Daniel Maturana, Dieter Fox, Nicholas Roy
Citations: 610 • 2016
Visual Odometry : Part II: Matching, Robustness, Optimization, and Applications
Friedrich Fraundorfer, Davide Scaramuzza
Citations: 606 • 2012
Mobile robot positioning: Sensors and techniques
J. Borenstein, H. R. Everett, Liang Feng, D.K. Wehe
Citations: 599 • 1997
Navigating Mobile Robots: Systems and Techniques
J. Borenstein, H. R. Everett, Liqiang Feng
Citations: 595 • 1996
Tightly Coupled 3D Lidar Inertial Odometry and Mapping
Haoyang Ye, Yuying Chen, Ming Liu
Citations: 568 • 2019
The event-camera dataset and simulator: Event-based data for pose estimation, visual odometry, and SLAM
Citations: 562 • 2017
Robust odometry estimation for RGB-D cameras
Christian Kerl, Jürgen Sturm, Daniel Cremers
Citations: 553 • 2013
University of Michigan North Campus long-term vision and lidar dataset
Nicholas Carlevaris‐Bianco, Arash K. Ushani, Ryan M. Eustice
Citations: 548 • 2015
Semi-dense Visual Odometry for a Monocular Camera
Jakob Engel, Jürgen Sturm, Daniel Cremers
Citations: 538 • 2013