STEP: State Estimator for Legged Robots Using a Preintegrated foot Velocity Factor
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Abstract (arXiv)
We propose a novel state estimator for legged robots, STEP, achieved through a novel preintegrated foot velocity factor. In the preintegrated foot velocity factor, the usual non-slip assumption is not adopted. Instead, the end effector velocity becomes observable by exploiting the body speed obtained from a stereo camera. In other words, the preintegrated end effector's pose can be estimated. Another advantage of our approach is that it eliminates the necessity for a contact detection step, unlike the typical approaches. The proposed method has also been validated in harsh-environment simulations and real-world experiments containing uneven or slippery terrains.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Feb 2022.
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Citing papers per year: 2024: 1; 2025: 2.
3 papers.
- 2024DreamWaQ++: Obstacle-Aware Quadrupedal Locomotion With Resilient Multi-Modal Reinforcement Learningcited by 6
- 2025Robust Localization, Mapping, and Navigation for Quadruped Robotscited by 2
- 2025Holistic Fusion: Task- and Setup-Agnostic Robot Localization and State Estimation with Factor Graphscited by 1
- 2025Robust Localization, Mapping, and Navigation for Quadruped Robots4 May 2025
- 2025Holistic Fusion: Task- and Setup-Agnostic Robot Localization and State Estimation with Factor Graphs8 Apr 2025
- 2024DreamWaQ++: Obstacle-Aware Quadrupedal Locomotion With Resilient Multi-Modal Reinforcement Learning29 Sep 2024