15 citations · 15 across the 8 of their papers we have counts for
5 papers · 1 filter
Beyond Kinematic Tracking: Preserving Expressive Characteristics in Humanoid Whole-Body Control
Lingfan Bao, Hanshang Zhu, Yan Pan +6
Whole-body control plays a crucial role in enabling humanoid robots to execute expressive motions. Faithful execution requires preserving both the intended action and its expressiv…
Reliability-Aware Sparse Route Memory for Round-Trip Vision-Language Navigation
Bojun Long, Lingfan Bao, Tianhu Peng +2
Vision-language navigation (VLN) is typically evaluated as a one-way task, although deployed robots may need to return after reaching a goal. We study continuous round-trip VLN and…
PAMoR: Parameterized Affective Motion Generation in Real Time for Humanoid Robots
Yan Pan, Lingfan Bao, Tianhu Peng +1
People read a humanoid robot's motion in social settings not only for the action performed but for the affect conveyed. Motion carrying that affect has so far been generated for hu…
SCDP: Learning Humanoid Locomotion from Partial Observations via Mixed-Observation Distillation
Milo Carroll, Tianhu Peng, Lingfan Bao +2
Distilling humanoid locomotion control from offline datasets into deployable policies remains a challenge, as existing methods rely on privileged full-body states that require comp…
A High-Fidelity Digital Twin for Robotic Manipulation Based on 3D Gaussian Splatting
Ziyang Sun, Lingfan Bao, Tianhu Peng +2
Developing high-fidelity, interactive digital twins is crucial for enabling closed-loop motion planning and reliable real-world robot execution, which are essential to advancing si…