Co-RaL: Complementary Radar-Leg Odometry with 4-DoF Optimization and Rolling Contact
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866909249408335872 |
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| author | Jung, Sangwoo Yang, Wooseong Kim, Ayoung |
| author_facet | Jung, Sangwoo Yang, Wooseong Kim, Ayoung |
| contents | 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 |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_05820 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Co-RaL: Complementary Radar-Leg Odometry with 4-DoF Optimization and Rolling Contact Jung, Sangwoo Yang, Wooseong Kim, Ayoung Robotics 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 |
| title | Co-RaL: Complementary Radar-Leg Odometry with 4-DoF Optimization and Rolling Contact |
| topic | Robotics |
| url | https://arxiv.org/abs/2407.05820 |