Embodied Vision
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ST-VIO tightly integrates visual, inertial, and dynamic motion constraints and calibrates the motion model online. © IEEE. Reprinted, with permission, from [
].
Visual-Inertial State Estimation with Online Adaptation of Mobile Robot Dynamics Models

In our works [
], we investigate visual-inertial odometry approaches that enable wheeled robots to estimate their 3D motion in real-time and adapt the kinematic or dynamic model of the robot online to variations of robot and terrain properties. Kin-VIO [
] adapts parameters of the mapping from velocity controls to an effective control command for a kinematic velocity-based motion model. In ST-VIO [
] a single-track dynamic model formulated as an ODE is used to predict robot motion. Several of its parameters which map steering angle and thrust commands to robot motion are calibrated online.
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Embodied Vision
Conference Paper
Online Calibration of a Single-Track Ground Vehicle Dynamics Model by Tight Fusion with Visual-Inertial Odometry
Li, H., Stueckler, J.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2024 (Published)
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Embodied Vision
Autonomous Motion
Movement Generation and Control
Conference Paper
Visual-Inertial and Leg Odometry Fusion for Dynamic Locomotion
Dhédin, V., Li, H., Khorshidi, S., Mack, L., Ravi, A. K. C., Meduri, A., Shah, P., Grimminger, F., Righetti, L., Khadiv, M., et al.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2023 (Published)
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Embodied Vision
Article
Visual-Inertial Odometry with Online Calibration of Velocity-Control Based Kinematic Motion Models
Li, H., Stueckler, J.
IEEE Robotics and Automation Letters, 7(3):6415-6422, July 2022, Accepted for oral presentation at IEEE ICRA 2023 (Published)
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Embodied Vision
Article
Visual-Inertial Mapping with Non-Linear Factor Recovery
Usenko, V., Demmel, N., Schubert, D., Stückler, J., Cremers, D.
IEEE Robotics and Automation Letters (RA-L), 5(2):422-429, 2020, presented at IEEE International Conference on Robotics and Automation (ICRA) 2020, preprint arXiv:1904.06504 (Published)
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