Real-time trajectory adaptation for quadrupedal locomotion using deep reinforcement learning
We present a control architecture for real-time adaptation and tracking of trajectories generated using a terrain-aware trajectory optimization solver. This approach enables us to circumvent the computationally exhaustive task of online trajectory optimization, and further introduces a control solut...
| Autores principales: | , , , , |
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| Formato: | Conference item |
| Lenguaje: | English |
| Publicado: |
IEEE
2021
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