22 citations · 22 across the 5 of their papers we have counts for
6 papers
PolyMorph: Learning Locomotion Policy for Cross-Embodiment Adaptation
Hyunsik Oh, Seunghun Jeon, Donghoon Youm +5
Reinforcement learning has enabled robust locomotion for legged robots, but learned policies are typically tied to a specific robot morphology and require additional engineering wh…
PAKE: Learning Whole-Body Loco-Manipulation with Partial Kinematic Embeddings
Zhengmao He, Moonkyu Jung, Hyeongjun Kim +4
Loco-manipulation has recently shown promising capabilities; however, achieving high-precision control, managing the high-dimensional action space induced by many degrees of freedo…
Learning Dynamic Pick-and-Place for a Legged Manipulator
Moonkyu Jung, Jiseong Lee, Zhengmao He +8
Legged manipulators extend robotic capabilities beyond static manipulation by integrating agile locomotion with versatile arm control. However, achieving precise manipulation while…
High-speed control and navigation for quadrupedal robots on complex and discrete terrain
Hyeongjun Kim, Hyunsik Oh, Jeongsoo Park +5
High-speed legged navigation in discrete and geometrically complex environments is a challenging task because of the high-degree-of-freedom dynamics and long-horizon, nonconvex nat…
Legged Robot State Estimation With Invariant Extended Kalman Filter Using Neural Measurement Network
Donghoon Youm, Hyunsik Oh, Suyoung Choi +2
This paper introduces a novel proprioceptive state estimator for legged robots that combines model-based filters and deep neural networks. Recent studies have shown that neural net…
Imitating and Finetuning Model Predictive Control for Robust and Symmetric Quadrupedal Locomotion
Donghoon Youm, Hyunyoung Jung, Hyeongjun Kim +3
Control of legged robots is a challenging problem that has been investigated by different approaches, such as model-based control and learning algorithms. This work proposes a nove…