Corpus ID: 232335514

iMHS: An Incremental Multi-Hypothesis Smoother

@article{Jiang2021iMHSAI,
  title={iMHS: An Incremental Multi-Hypothesis Smoother},
  author={Fan Jiang and V. Agrawal and Russell Buchanan and M. Fallon and F. Dellaert},
  journal={ArXiv},
  year={2021},
  volume={abs/2103.13178}
}
State estimation of multi-modal hybrid systems is an important problem with many applications in the field robotics. However, incorporating discrete modes in the estimation process is hampered by a potentially combinatorial growth in computation. In this paper we present a novel incremental multi-hypothesis smoother based on eliminating a hybrid factor graph into a multi-hypothesis Bayes tree, which represents possible discrete state sequence hypotheses. Following iSAM, we enable incremental… Expand

References

SHOWING 1-10 OF 30 REFERENCES
State estimation for hybrid systems: applications to aircraft tracking
  • 85
  • PDF
MH-iSAM2: Multi-hypothesis iSAM using Bayes Tree and Hypo-tree
  • Ming Hsiao, M. Kaess
  • Computer Science
  • 2019 International Conference on Robotics and Automation (ICRA)
  • 2019
  • 12
  • PDF
Factor Graphs for Robot Perception
  • 128
  • PDF
State Estimation for Legged Robots - Consistent Fusion of Leg Kinematics and IMU
  • 109
  • PDF
Robust Legged Robot State Estimation Using Factor Graph Optimization
  • 17
  • PDF
iSAM: Incremental Smoothing and Mapping
  • 891
  • PDF
Learning and inference in parametric switching linear dynamic systems
  • 47
  • PDF
Incremental smoothing and mapping
  • 362
  • PDF
An Efficient Implementation of Reid's Multiple Hypothesis Tracking Algorithm and Its Evaluation for the Purpose of Visual Tracking
  • I. Cox, S. Hingorani
  • Mathematics, Computer Science
  • IEEE Trans. Pattern Anal. Mach. Intell.
  • 1996
  • 719
  • PDF
Multiple-model adaptive estimation using a residual correlation Kalman filter bank
  • 214
  • PDF
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