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Alexander Reske

2 accepted papers

2024

Exploring Constrained Reinforcement Learning Algorithms for Quadrupedal Locomotion

IROS 2024poster

Shifting from traditional control strategies to Deep Reinforcement Learning (RL) for legged robots poses inherent challenges, especially when addressing real-world physical constraints during training. While high-fidelity simulations provide significant benefits, they often bypass these essential ph…

Cited by 1SourceScholar
2021

Imitation Learning from MPC for Quadrupedal Multi-Gait Control

ICRA 2021poster

We present a learning algorithm for training a single policy that imitates multiple gaits of a walking robot. To achieve this, we use and extend MPC-Net, which is an Imitation Learning approach guided by Model Predictive Control (MPC). The strategy of MPC-Net differs from many other approaches since…

Cited by 52SourceScholar