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Research on balance control of humanoid robot based on inertial measurement unit
- 1 School of Engineering, Penn State University, PA, USA
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Abstract
This collection of papers investigates different uses of IMU (Inertial Measurement Unit) technology in areas such as robotics, industry, and rehabilitation. In applications involving the compensation of robot flexibility and energetic balance control, IMU sensors, when paired with geometric models and Extended Kalman Filters (EKF), substitute conventional force sensors. This substitution enhances the real-time estimation of contact forces and moments. These methods, which operate at high frequencies, greatly strengthen the robot's balance and its ability to withstand external disturbances. Another key focus of the research is joint state estimation and posture control in robots. Here, IMU data, combined with other models, allows for accurate motion tracking and boosts energetic stability. Importantly, the fusion of IMU with vision and force sensors further improves motion capture accuracy. Utilizing IMU technology is not limited to robotics. In pediatric rehabilitation, it enhances motion recognition and engagement by giving therapists real-time feedback, thereby overcoming the limitations of vision-based systems such as Kinect. Similarly, in industrial contexts, wearable devices that use IMUs surpass traditional vision systems in gesture recognition within complex environments, yielding greater accuracy and energy efficiency. This illustrates the adaptability of IMUs across various domains, including robotic control, healthcare, and manufacturing processes.
Keywords
Inertial Measurement Units, Flexibility Compensation, Dynamic Balance Control, Robot Motion Tracking, Extended Kalman Filter
[1]. Mifsud, A., Benallegue, M., & Lamiraux, F. (2015). Estimation of contact forces and floating base kinematics of a humanoid robot using only Inertial Measurement Units. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 3374-3379).
[2]. Benallegue, M., & Lamiraux, F. (2015). Estimation and Stabilization of Humanoid Flexibility Deformation Using Only Inertial Measurement Units and Contact Information. International Journal of Humanoid Robotics, 12(03), 1550025.
[3]. Benallegue, M., & Lamiraux, F. (2014). Humanoid flexibility deformation can be efficiently estimated using only inertial measurement units and contact information. In Proceedings of the IEEE-RAS International Conference on Humanoid Robots (pp. 246-251).
[4]. Benallegue, M., Mifsud, A., & Lamiraux, F. (2015). Fusion of force-torque sensors, inertial measurements units and proprioception for a humanoid kinematics-dynamics observation. In Proceedings of the IEEE-RAS 15th International Conference on Humanoid Robots (pp. 664-669).
[5]. Ferrete Ribeiro, N., & Santos, C. P. (2017). Inertial measurement units: A brief state of the art on gait analysis. In Proceedings of the IEEE 5th Portuguese Meeting on Bioengineering (pp. 1-4).
[6]. Mifsud, A., Benallegue, M., & Lamiraux, F. (2016). Stabilization of a compliant humanoid robot using only Inertial Measurement Units with a viscoelastic reaction mass pendulum model. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 5405-5410).
[7]. Rotella, N., Mason, S., Schaal, S., & Righetti, L. (2016). Inertial sensor-based humanoid joint state estimation. In Proceedings of the IEEE International Conference on Robotics and Automation (pp. 1825-1831).
[8]. Samatas, G. G., & Pachidis, T. P. (2022). Inertial Measurement Units (IMUs) in Mobile Robots over the Last Five Years: A Review. Designs, 6(1), 17. https://doi.org/10.3390/designs6010017
[9]. Kim, S. K., Hong, S., & Kim, D. (2009). A walking motion imitation framework of a humanoid robot by human walking recognition from IMU motion data. In Proceedings of the 9th IEEE-RAS International Conference on Humanoid Robots (pp. 343-348).
[10]. Zebenay, M., Lippi, V., & Mergener, T. (2015). Human-like humanoid robot posture control. In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics (pp. 304-309).
[11]. Guneysu, A., Arnrich, B., & Ersoy, C. (2015). Children's rehabilitation with humanoid robots and wearable inertial measurement units. In Proceedings of the 9th International Conference on Pervasive Computing Technologies for Healthcare (pp. 249-252).
[12]. Roda-Sanchez, L., Garrido-Hidalgo, C., García, A. S., Olivares, T., & Fernández-Caballero, A. (2023). Comparison of RGB-D and IMU-based gesture recognition for human-robot interaction in remanufacturing. The International Journal of Advanced Manufacturing Technology, 124, 3099-3111. https://doi.org/10.1007/s00170-021-08125-9
Cite this article
Zhang,Z. (2025). Research on balance control of humanoid robot based on inertial measurement unit. Applied and Computational Engineering,136,8-14.
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