Tunable Impact and Vibration Absorbing Neck for Robust Visual-Inertial State Estimation for Dynamic Legged Robots
Name
Tunable_Impact_and_Vibration_Absorbing_Neck_for_Robust_Visual-Inertial_State_Estimation_for_Dynamic_Legged_Robots.pdf
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5.92 MB
Format
Adobe PDF
Checksum (MD5)
6d4354c5cd276f02f7fe095eab19a637
Author(s)
Kim, Taekyun
Kim, Sangbae
Lee, Dongjun
Date Issued
March 2023
Journal
IEEE Robotics and Automation Letters
Publisher
Institute of Electrical and Electronics Engineers
Citation
T. Kim, S. Kim and D. Lee, "Tunable Impact and Vibration Absorbing Neck for Robust Visual-Inertial State Estimation for Dynamic Legged Robots," in IEEE Robotics and Automation Letters, vol. 8, no. 3, pp. 1431-1438, March 2023.
Version
Final published version
Abstract
We propose a new neck design for legged robots to achieve robust visual-inertial state estimation in dynamic locomotion. While visual-inertial state estimation is widely used in robotics, it has a problem of being disturbed by the impacts and vibration generated when legged robots move dynamically. The use of rubber dampers may be a solution, but even if the dampers are proper for some gaits, they may be excessively deformed or resonated at certain frequencies during other gait locomotion since they are not tunable. To address this problem, we develop a tunable neck system that absorbs the impacts and vibration during diverse gait locomotions. This neck system consists of two components: 1) a suspension mechanism that compensates for the weight of the head equipped with a camera and IMU (inertial measurement unit), absorbs the impacts and the head motion of high frequencies including vibration as a fixed low-pass filter; and 2) a dynamic vibration absorber (DVA) that can be reactively-adjusted to diverse gait frequencies to alleviate excessive head movements. We present a dynamics analysis of the neck system and show how to adjust the target frequency of the system. Simulation and experimental validation are performed to verify the effect of the proposed neck design, manifesting superior estimation performance and robustness across diverse gaits.
Subjects
Artificial Intelligence
Control and Optimization
Computer Science Applications
Computer Vision and Pattern Recognition
Mechanical Engineering
Human-Computer Interaction
Biomedical Engineering
Control and Systems Engineering
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/lra.2023.3240369
