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20242026
most citedFR-Net: Learning Robust Quadrupedal Fall Recovery on Challenging Terrains through Mass-Contact Prediction

9 citations · 9 across the 11 of their papers we have counts for

collaborators
Showing 2026 · cs.ROShow all

7 papers · 2 filters

cs.RO2026

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…

cs.RO2026

MILD: Tractable Terrain Modeling for Learning Improved Bipedal Locomotion on Deformable Surfaces

Zeren Luo, Jiahui Zhang, Zhe Xu +6

Enabling robots to walk on yielding terrain is vital for applications ranging from disaster response to planetary exploration. While bipedal robots hold immense potential, their lo…

cs.RO2026

RoboNaldo: Accurate, Stable and Powerful Humanoid Soccer Shooting via Motion-Guided Curriculum Reinforcement Learning

Yichao Zhong, Yidan Lu, Yuhang Lu +9

Elite humanoid soccer shooting requires whole-body stability, high-impulse whole-body interactions, and accuracy to targets. Motion tracking-driven reinforcement learning (RL) prov…

cs.RO2026

Unified Walking, Running, and Recovery for Humanoids via State-Dependent Adversarial Motion Priors

Yidan Lu, Yichao Zhong, Liu Zhao +2

We propose a unified reinforcement learning framework that enables a single policy to perform walking, running, and fall recovery on the Unitree G1 humanoid robot, validated on phy…

cs.RO2026

SMASH: Mastering Scalable Whole-Body Skills for Humanoid Ping-Pong with Egocentric Vision

Junli Ren, Yinghui Li, Kai Zhang +12

Existing humanoid table tennis systems remain limited by their reliance on external sensing and their inability to achieve agile whole-body coordination for precise task execution.…

cs.RO2026

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…

cs.RO2026

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…