6 citations · 10 across the 7 of their papers we have counts for
7 papers
On constructive extractability of measurable selectors of set-valued maps
Pavel Osinenko, Stefan Streif
This paper investigates the possibility of constructive extraction of measurable selector from set-valued maps which may commonly arise in viability theory, optimal control, discon…
Combining model-predictive control and predictive reinforcement learning for stable quadrupedal robot locomotion
Vyacheslav Kovalev, Anna Shkromada, Henni Ouerdane +1
Stable gait generation is a crucial problem for legged robot locomotion as this impacts other critical performance factors such as, e.g. mobility over an uneven terrain and power c…
Experimental verification of an online traction parameter identification method
Alexander Kobelski, Pavel Osinenko, Stefan Streif
Traction parameters, that characterize the ground-wheel contact dynamics, are the central factor in the energy efficiency of vehicles. To optimize fuel consumption, reduce wear of…
A stabilizing reinforcement learning approach for sampled systems with partially unknown models
Lukas Beckenbach, Pavel Osinenko, Stefan Streif
Reinforcement learning is commonly associated with training of reward-maximizing (or cost-minimizing) agents, in other words, controllers. It can be applied in model-free or model-…
A framework for online, stabilizing reinforcement learning
Grigory Yaremenko, Georgiy Malaniya, Pavel Osinenko
Online reinforcement learning is concerned with training an agent on-the-fly via dynamic interaction with the environment. Here, due to the specifics of the application, it is not…
A note on Brehm's extension theorem
Pavel Osinenko
Brehm's extension theorem states that a non-expansive map on a finite subset of a Euclidean space can be extended to a piecewise-linear map on the entire space. In this note, it is…