On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Simultaneous Localization and Map-Building Using Active Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Two years of Visual Odometry on the Mars Exploration Rovers: Field Reports
Journal of Field Robotics - Special Issue on Space Robotics
MonoSLAM: Real-Time Single Camera SLAM
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving the Agility of Keyframe-Based SLAM
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Parallel Tracking and Mapping for Small AR Workspaces
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
The New College Vision and Laser Data Set
International Journal of Robotics Research
Nonlinear Mean Shift over Riemannian Manifolds
International Journal of Computer Vision
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Faster and Better: A Machine Learning Approach to Corner Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
PSO-FastSLAM: an improved FastSLAM framework using particle swarm optimization
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Multiswarm particle filter for vision based SLAM
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
RSLAM: A System for Large-Scale Mapping in Constant-Time Using Stereo
International Journal of Computer Vision
Inverse Depth Parametrization for Monocular SLAM
IEEE Transactions on Robotics
Multiswarms, exclusion, and anti-convergence in dynamic environments
IEEE Transactions on Evolutionary Computation
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Conventional particle filtering-based visual ego-motion estimation or visual odometry often suffers from large local linearization errors in the case of abrupt camera motion. The main contribution of this paper is to present a novel particle filtering-based visual ego-motion estimation algorithm that is especially robust to the abrupt camera motion. The robustness to the abrupt camera motion is achieved by multi-layered importance sampling via particle swarm optimization (PSO), which iteratively moves particles to higher likelihood region without local linearization of the measurement equation. Furthermore, we make the proposed visual ego-motion estimation algorithm in real-time by reformulating the conventional vector space PSO algorithm in consideration of the geometry of the special Euclidean group SE(3), which is a Lie group representing the space of 3-D camera poses. The performance of our proposed algorithm is experimentally evaluated and compared with the local linearization and unscented particle filter-based visual ego-motion estimation algorithms on both simulated and real data sets.