1 citations · 1 across the 6 of their papers we have counts for
7 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…
DELTA: Deformable Elevation-Based Local Terrain Attention Encoder for Sparse-Terrain Quadrupedal Locomotion
Sanghyun Park, Moonkyu Jung, Jemin Hwangbo
Stable quadrupedal locomotion on sparse terrain requires selecting state-relevant terrain evidence for precise foot placement. Model-based foothold planners provide precise foothol…
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…
Learning Whole-body Manipulation for Quadrupedal Robot
Seunghun Jeon, Moonkyu Jung, Suyoung Choi +2
We propose a learning-based system for enabling quadrupedal robots to manipulate large, heavy objects using their whole body. Our system is based on a hierarchical control strategy…
Not Only Rewards But Also Constraints: Applications on Legged Robot Locomotion
Yunho Kim, Hyunsik Oh, Jeonghyun Lee +5
Several earlier studies have shown impressive control performance in complex robotic systems by designing the controller using a neural network and training it with model-free rein…