Meta-Learning for Fast Adaptive Locomotion with Uncertainties in Environments and Robot Dynamics
Timothée Anne,Jack Wilkinson,Zhibin Li,Timothée Anne,Jack Wilkinson,Zhibin Li
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 trajectories, and then applies the optimal actions to maximize the reward. To achieve online model adaptation...
