Lowering reinforcement learning barriers for quadruped locomotion in the task space
In contrast to traditional methods like model predictive control (MPC), deep reinforcement learning (DRL) offers a simpler and less model- intensive option to develop quadruped locomotion policies. However, DRL presents a steep learning curve and a large barrier to entry for novice researchers. This...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://www.matec-conferences.org/articles/matecconf/pdf/2024/18/matecconf_rapdasa2024_04007.pdf |
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