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Bibliography

Journal Article

Application of the Method of Maximum Likelihood to Identification of Bipedal Walking Robots

Dolinský Kamil, Čelikovský Sergej

: IEEE Transactions on Control Systems Technology vol.26, 4 (2018), p. 1500-1507

: GA17-04682S, GA ČR

: Control, identification, maximum likelihood (ML), walking robots

: 10.1109/TCST.2017.2709277

: http://library.utia.cas.cz/separaty/2018/TR/dolinsky-0475621.pdf

(eng): This brief studies the problem of parameter estimation and model identification for a class of underactuated mechanical systems modeled via the Euler–Lagrange formalism, such as underactuated walking robots. This problem is closely related with the measurement of the absolute orientation during walking. A novel identification method suited for this problem\nwas proposed. The method takes advantage of the linear structure of the model with respect to estimated parameters. The resulting estimator is calculated iteratively and maximizes\nthe likelihood of the data. The method was tested on both simulated and experimental data. Simulation was carried out for an underactuated walking robot with a distance meter to\nmeasure absolute orientation. Laboratory experiment was carried out on a leg of a laboratory walking robot model equipped with a three-axis accelerometer and gyroscope to measure absolute\norientation. The method performs favorably in comparison with other benchmark estimation algorithms and both the simulation example and the laboratory experiment confirmed its high\npotential for the use in identification of underactuated robotic walkers.

: BC

: 20205

2019-01-07 08:39