Double window optimisation for constant time visual SLAM
@article{Strasdat2011DoubleWO, title={Double window optimisation for constant time visual SLAM}, author={Hauke Malte Strasdat and Andrew J. Davison and J. M. M. Montiel and Kurt Konolige}, journal={2011 International Conference on Computer Vision}, year={2011}, pages={2352-2359} }
We present a novel and general optimisation framework for visual SLAM, which scales for both local, highly accurate reconstruction and large-scale motion with long loop closures. [] Key Method Our algorithm automatically builds a suitable connected graph of keyposes and constraints, dynamically selects inner and outer window membership and optimises both simultaneously. We demonstrate in extensive simulation experiments that our method approaches the accuracy of offline bundle adjustment while maintaining…
Figures from this paper
286 Citations
Image based optimisation without global consistency for constant time monocular visual SLAM
- Computer Science2015 IEEE International Conference on Robotics and Automation (ICRA)
- 2015
This paper presents a monocular visual SLAM system that does not require a globally consistent 3D model, and merely optimises relative pose parameters for pairs of keyframes that overlap on the scene, providing accurate local information at the expense of global consistency.
Hybrid Monocular SLAM Using Double Window Optimization
- Computer ScienceIEEE Robotics and Automation Letters
- 2021
This letter presents a hybrid framework, both in front-end and back-end, for monocular simultaneous localization and mapping (SLAM), capable of utilizing the robustness of feature matching and the accuracy of direct alignment, leading to a comparable performance with the state-of-the-arts.
ORB-SLAM: A Versatile and Accurate Monocular SLAM System
- Computer ScienceIEEE Transactions on Robotics
- 2015
A survival of the fittest strategy that selects the points and keyframes of the reconstruction leads to excellent robustness and generates a compact and trackable map that only grows if the scene content changes, allowing lifelong operation.
Multi-camera visual SLAM for autonomous navigation of micro aerial vehicles
- Computer ScienceRobotics Auton. Syst.
- 2017
ElasticFusion: Dense SLAM Without A Pose Graph
- Computer ScienceRobotics: Science and Systems
- 2015
This system is capable of capturing comprehensive dense globally consistent surfel-based maps of room scale environments explored using an RGB-D camera in an incremental online fashion, without pose graph optimisation or any postprocessing steps.
RGB-D dense SLAM with keyframe-based method
- Computer ScienceOther Conferences
- 2018
This paper proposes a new RGB-D dense SLAM system, which produces better results than the state-of-the-art systems in terms of the accuracy of the produced camera trajectories.
Recovering Stable Scale in Monocular SLAM Using Object-Supplemented Bundle Adjustment
- Computer ScienceIEEE Transactions on Robotics
- 2018
This work describes a monocular approach that in addition to point measurements also considers object detections to resolve scale ambiguity and drift in a single-camera simultaneous localization and mapping system.
DynaMiTe: A Dynamic Local Motion Model with Temporal Constraints for Robust Real-Time Feature Matching
- Computer ScienceArXiv
- 2020
The lightweight pipeline DynaMiTe is presented, which is agnostic to the descriptor input and leverages spatial-temporal cues with efficient statistical measures, outperforming state-of-the-art matching methods while being computationally more efficient.
Batch based Monocular SLAM for Egocentric Videos
- Computer ScienceArXiv
- 2017
This work proposes a novel batch mode structure from motion based technique for robust SLAM in such scenarios, and presents both qualitative and quantitative comparison of the method on various public first and third person video datasets, to establish the robustness and accuracy of the algorithm over the state of the art.
Long range monocular SLAM
- Computer Science
- 2017
This thesis explores approaches to two problems in the frame-rate computation of a priori unknown 3D scene structure and camera pose using a single camera, or monocular simultaneous localisation and mapping, and develops sparsified direct methods for monocular SLAM.
References
SHOWING 1-10 OF 19 REFERENCES
Scale Drift-Aware Large Scale Monocular SLAM
- Computer ScienceRobotics: Science and Systems
- 2010
This paper describes a new near real-time visual SLAM system which adopts the continuous keyframe optimisation approach of the best current stereo systems, but accounts for the additional challenges presented by monocular input and presents a new pose-graph optimisation technique which allows for the efficient correction of rotation, translation and scale drift at loop closures.
FrameSLAM: From Bundle Adjustment to Real-Time Visual Mapping
- Computer ScienceIEEE Transactions on Robotics
- 2008
The skeleton of this framework is a reduced nonlinear system that is a faithful approximation of the larger system and can be used to solve large loop closures quickly, as well as forming a backbone for data association and local registration.
Parallel Tracking and Mapping for Small AR Workspaces
- Computer Science2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
- 2007
A system specifically designed to track a hand-held camera in a small AR workspace, processed in parallel threads on a dual-core computer, that produces detailed maps with thousands of landmarks which can be tracked at frame-rate with accuracy and robustness rivalling that of state-of-the-art model-based systems.
Highly scalable appearance-only SLAM - FAB-MAP 2.0
- Computer ScienceRobotics: Science and Systems
- 2009
A new formulation of appearance-only SLAM suitable for very large scale navigation that naturally incorporates robustness against perceptual aliasing is described and demonstrated performing reliable online appearance mapping and loop closure detection over a 1,000 km trajectory.
Real Time Localization and 3D Reconstruction
- Mathematics2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)
- 2006
A method that estimates the motion of a calibrated camera and the tridimensional geometry of the environment and the introduction of a fast and local bundle adjustment method that ensures both good accuracy and consistency of the estimated camera poses along the sequence is described.
Vast-scale Outdoor Navigation Using Adaptive Relative Bundle Adjustment
- Computer ScienceInt. J. Robotics Res.
- 2010
A new relative bundle adjustment is derived which, instead of optimizing in a single Euclidean space, works in a metric space defined by a manifold, and it is shown experimentally that it is possible to solve for the full maximum-likelihood solution incrementally in constant time, even at loop closure.
Online environment mapping
- Computer ScienceCVPR 2011
- 2011
The paper proposes a vision based online mapping of large-scale environments using a hybrid representation of a fully metric Euclidean environment map and a topological map that achieves scalability by solving the local registration through embedding neighboring keyframes and landmarks into a Euclidan space.
Adaptive relative bundle adjustment
- Computer ScienceRobotics: Science and Systems
- 2009
This paper derives a new relative bundle adjustment, which instead of optimizing in a single Euclidean space, works in a metric-space defined by a connected Riemannian manifold, and shows experimentally that it is possible to solve for the full ML solution incrementally in constant time – even at loop closure.
On measuring the accuracy of SLAM algorithms
- Computer ScienceAuton. Robots
- 2009
A framework for analyzing the results of a SLAM approach based on a metric for measuring the error of the corrected trajectory is proposed, which overcomes serious shortcomings of approaches using a global reference frame to compute the error.
G2o: A general framework for graph optimization
- Computer Science2011 IEEE International Conference on Robotics and Automation
- 2011
G2o, an open-source C++ framework for optimizing graph-based nonlinear error functions, is presented and demonstrated that while being general g2o offers a performance comparable to implementations of state-of-the-art approaches for the specific problems.