LeSTA: Learning Self-supervised Traversabiltiy with Navigation Experiences of Mobile Robots

💻 Installation | 🎥 Video | 📖 Paper (RA-L) | 📁 Dataset

🔥 README will be updated soon (About 1 week). Stay tuned! 🔥

What is LeSTA

LeSTA aims to learn robot-specific traversability in a self-supervised manner by using a short period of manual driving.

How to use LeSTA

Citation

Thank you for citing our paper if this helps your research projects:

Ikhyeon Cho, and Woojin Chung. 'Learning Self-Supervised Traversability With Navigation Experiences of Mobile Robots: A Risk-Aware Self-Training Approach', IEEE Robotics and Automation Letters, 2024.

@article{cho2024learning,
  title={Learning Self-Supervised Traversability With Navigation Experiences of Mobile Robots: A Risk-Aware Self-Training Approach}, 
  author={Cho, Ikhyeon and Chung, Woojin},
  journal={IEEE Robotics and Automation Letters}, 
  year={2024},
  volume={9},
  number={5},
  pages={4122-4129},
  doi={10.1109/LRA.2024.3376148}
}

You can also check the paper of our baseline:

Hyunsuk Lee, and Woojin Chung. 'A Self-Training Approach-Based Traversability Analysis for Mobile Robots in Urban Environments', IEEE International Conference on Robotics and Automation (ICRA), 2021.

@inproceedings{lee2021self,
  title={A self-training approach-based traversability analysis for mobile robots in urban environments},
  author={Lee, Hyunsuk and Chung, Woojin},
  booktitle={2021 IEEE International Conference on Robotics and Automation (ICRA)},
  pages={3389--3394},
  year={2021},
  organization={IEEE}
}