3 accepted papers
Humanoid robots could replace humans in hazardous situations but most of such situations are equally dangerous for them, which means that they have a high chance of being damaged and falling. We hypothesize that humanoid robots would be mostly used in buildings, which makes them likely to be close t
This work developed meta-learning control policies to achieve fast online adaptation to different changing conditions, which generate diverse and robust locomotion. The proposed method updates the interaction model constantly, samples feasible sequences of actions of estimated state-action trajector…
Meta-learning algorithms can accelerate the model-based reinforcement learning (MBRL) algorithms by finding an initial set of parameters for the dynamical model such that the model can be trained to match the actual dynamics of the system with only a few data-points. However, in the real world, a ro…