Machine Learning for Visual Navigation of Unmanned Ground Vehicles

@article{Lenskiy2016MachineLF,
  title={Machine Learning for Visual Navigation of Unmanned Ground Vehicles},
  author={Artem Lenskiy and Jong-Soo Lee},
  journal={ArXiv},
  year={2016},
  volume={abs/1604.02485}
}
The use of visual information for the navigation of unmanned ground vehicles in a cross-country environment recently received great attention. However, until now, the use of textural information has been somewhat less effective than color or laser range information. This manuscript reviews the recent achievements in cross-country scene segmentation and addresses their shortcomings. It then describes a problem related to classification of high dimensional texture features. Finally, it compares… Expand
3 Citations

References

SHOWING 1-10 OF 55 REFERENCES
Natural terrain classification using 3-d ladar data
Combining laser range, color, and texture cues for autonomous road following
  • C. Rasmussen
  • Computer Science, Engineering
  • Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292)
  • 2002
Neural Network Based Terrain Classification Using Wavelet Features
Learning Outdoor Color Classification
  • R. Manduchi
  • Mathematics, Medicine
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2006
Speeded-Up Robust Features (SURF)
A direct adaptive method for faster backpropagation learning: the RPROP algorithm
Stanley: The robot that won the DARPA Grand Challenge
...
1
2
3
4
5
...