9 citations · 9 across the 11 of their papers we have counts for
12 papers · 1 filter
HiPHI: A Large-Scale Benchmark for High-Precision Human Motion and Object-Interaction
Jiahao Ji, Ji Ma, Runhan Zhang +12
Humanoid intelligence requires learning over an extremely diverse space of whole-body motions and physically grounded interactions. However, existing embodied datasets remain funda…
Unified Motion Retargeting for Humanoids with Learned Point Cloud Correspondence
Hanyang Cao, Yuetong Fang, Taesoo Kwon +10
Humanoid learning increasingly relies on transforming vast and diverse human motion data into high-quality robot reference trajectories. However, retargeting human motion to humano…
PFM-HR: Pose Flow Matching for Humanoid Robots
Yukang Gao, Yi Gu, Yangchen Zhou +9
Motion priors improve reinforcement learning for physics-based humanoid tracking, but temporal priors require ordered motion clips, while pose priors provide limited guidance for p…
Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space
Zeren Luo, Jiahui Zhang, Yimin Han +4
Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating this behavior in quadrupedal robots has been a longstanding challe…
OmniContact: Chaining Meta-Skills via Contact Flow for Generalizable Humanoid Loco-Manipulation
Runyi Yu, Xiaoyi Lin, Ji Ma +11
Learning long-horizon humanoid loco-manipulation poses a dual challenge: it requires not only the robust execution of meta-skills but also their seamless, closed-loop chaining equi…
Co-jump: Cooperative Jumping with Quadrupedal Robots via Multi-Agent Reinforcement Learning
Shihao Dong, Yeke Chen, Zeren Luo +8
While single-agent legged locomotion has witnessed remarkable progress, individual robots remain fundamentally constrained by physical actuation limits. To transcend these boundari…
Learning Human-Like Badminton Skills for Humanoid Robots
Yeke Chen, Shihao Dong, Xiaoyu Ji +12
Realizing versatile and human-like performance in high-demand sports like badminton remains a formidable challenge for humanoid robotics. Unlike standard locomotion or static manip…
Like Playing a Video Game: Spatial-Temporal Optimization of Foot Trajectories for Controlled Football Kicking in Bipedal Robots
Wanyue Li, Ji Ma, Minghao Lu +1
Humanoid robot soccer presents several challenges, particularly in maintaining system stability during aggressive kicking motions while achieving precise ball trajectory control. C…
MARG: MAstering Risky Gap Terrains for Legged Robots with Elevation Mapping
Yinzhao Dong, Ji Ma, Liu Zhao +2
Deep Reinforcement Learning (DRL) controllers for quadrupedal locomotion have demonstrated impressive performance on challenging terrains, allowing robots to execute complex skills…
FR-Net: Learning Robust Quadrupedal Fall Recovery on Challenging Terrains through Mass-Contact Prediction
Yidan Lu, Yinzhao Dong, Jiahui Zhang +2
Fall recovery for legged robots remains challenging, particularly on complex terrains where traditional controllers fail due to incomplete terrain perception and uncertain interact…
In-between Motion Generation Based Multi-Style Quadruped Robot Locomotion
Yuanhao Chen, Liu Zhao, Ji Ma +1
Quadruped robots face persistent challenges in achieving versatile locomotion due to limitations in reference motion data diversity. To address these challenges, we introduce an in…
Learning an Adaptive Fall Recovery Controller for Quadrupeds on Complex Terrains
Yidan Lu, Yinzhao Dong, Ji Ma +2
Legged robots have shown promise in locomotion complex environments, but recovery from falls on challenging terrains remains a significant hurdle. This paper presents an Adaptive F…