@inproceedings{li_robust_2017,
	title = {Robust foot placement control for dynamic walking using online parameter estimation},
	url = {https://hdl.handle.net/20.500.11820/5b95ed2f-caba-4660-93b7-45ef0942a065},
	doi = {10.1109/HUMANOIDS.2017.8239552},
	abstract = {This paper presents an estimation scheme to control foot placement for achieving a desired dynamic walking velocity in presence of sensor and model errors. Inevitable discrepancies, such as sensors$^{\textrm{5}}$ noise, delay, and modelling errors, degrade the performance of model-based control methods or even cause instabilities. To resolve these issues, an on-line parameter estimation approach based on Tikhonov regularisation is formulated using measurement data, which is particularly robust for more accurately approximating the dynamics. The proposed scheme initially uses the foot placement predicted by the linear inverted pendulum model, while the control parameters are being optimised using adequate measurements to represent the real dynamics within and in-between steps; and then, the estimation based control is used to predict the future foot placement accurately in the presence of discrepancies.},
	booktitle = {{IEEE} {International} {Conference} on {Humanoid} {Robotics}},
	author = {Li, Qingbiao and Chatzinikolaidis, Iordanis and Yang, Yiming and Vijayakumar, Sethu and Li, Zhibin},
	month = nov,
	year = {2017},
	pages = {165--170},
}

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