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cs.RO2024
CusADi: A GPU Parallelization Framework for Symbolic Expressions and Optimal Control
Se Hwan Jeon, Seungwoo Hong, Ho Jae Lee +2
The parallelism afforded by GPUs presents significant advantages in training controllers through reinforcement learning (RL). However, integrating model-based optimization into thi…
cs.RO2024
Integrating Model-Based Footstep Planning with Model-Free Reinforcement Learning for Dynamic Legged Locomotion
Ho Jae Lee, Seungwoo Hong, Sangbae Kim
In this work, we introduce a control framework that combines model-based footstep planning with Reinforcement Learning (RL), leveraging desired footstep patterns derived from the L…