4 papers · 1 filter
RuN: Residual Policy for Natural Humanoid Locomotion
Qingpeng Li, Chengrui Zhu, Yanming Wu +4
Enabling humanoid robots to achieve natural and dynamic locomotion across a wide range of speeds, including smooth transitions from walking to running, presents a significant chall…
L2Calib: -Manifold Reinforcement Learning for Robust Extrinsic Calibration with Degenerate Motion Resilience
Baorun Li, Chengrui Zhu, Siyi Du +5
Extrinsic calibration is essential for multi-sensor fusion, existing methods rely on structured targets or fully-excited data, limiting real-world applicability. Online calibration…
LITE: A Learning-Integrated Topological Explorer for Multi-Floor Indoor Environments
Junhao Chen, Zhen Zhang, Chengrui Zhu +4
This work focuses on multi-floor indoor exploration, which remains an open area of research. Compared to traditional methods, recent learning-based explorers have demonstrated sign…
Efficient Learning of A Unified Policy For Whole-body Manipulation and Locomotion Skills
Dianyong Hou, Chengrui Zhu, Zhen Zhang +3
Equipping quadruped robots with manipulators provides unique loco-manipulation capabilities, enabling diverse practical applications. This integration creates a more complex system…