Co-RaL: Complementary Radar-Leg Odometry with 4-DoF Optimization and Rolling Contact
<|reference_start|>Co-RaL: Complementary Radar-Leg Odometry with 4-DoF Optimization and Rolling Contact: Robust and accurate localization in challenging environments is becoming crucial for SLAM. In this paper, we propose a unique sensor configuration for precise and robust odometry by integrating chip radar and a legged robot. Specifically, we introduce a tightly coupled radar-leg odometry algorithm for complementary drift correction. Adopting the 4-DoF optimization and decoupled RANSAC to mmWave chip radar significantly enhances radar odometry beyond the existing method, especially z-directional even when using a single radar. For the leg odometry, we employ rolling contact modeling-aided forward kinematics, accommodating scenarios with the potential possibility of contact drift and radar failure. We evaluate our method by comparing it with other chip radar odometry algorithms using real-world datasets with diverse environments while the datasets will be released for the robotics community. https://github.com/SangwooJung98/Co-RaL-Dataset<|reference_end|>
@article{jung2024co-ral:,
    title={Co-RaL: Complementary Radar-Leg Odometry with 4-DoF Optimization and
  Rolling Contact},
    author={Sangwoo Jung, Wooseong Yang, Ayoung Kim},
    journal={arXiv preprint arXiv:2407.05820},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.05820},
    primaryClass={cs.RO}
}