  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
