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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…
TRACE: Learned Proprioceptive Odometry for Legged Robots under Unreliable Contact Conditions
Taehyeon Kong, Woojin Kim, Jemin Hwangbo
In this paper, we present TRACE (Tokenized Robust Attention for Contact-Aware Estimation), an end-to-end learned proprioceptive odometry estimator for legged robots under unreliabl…
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…
Learning Quadrupedal Locomotion for a Heavy Hydraulic Robot Using an Actuator Model
Minho Lee, Hyeonseok Kim, Jin Tak Kim +4
The simulation-to-reality (sim-to-real) transfer of large-scale hydraulic robots presents a significant challenge in robotics because of the inherent slow control response and comp…