Sangwoo Jung, Wooseong Yang and Ayoung Kim, Co-Ral, IROS 2024
[Paper Link]
arxiv.org/abs/2407.05820
[Dataset Link]
github.com/SangwooJung98/Co-R...
[Abstract]
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. github.com/SangwooJung98/Co-R...
Негізгі бет Ғылым және технология Co-RaL: Complementary Radar-Leg Odometry with 4-DoF Optimization and Rolling Contact
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