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cs.RO2026

Behavior Foundations for Quadruped Robots: ABot-C0 Technical Report

Xufeng Zhao, Fuzhi Yang, Jianhui Chen +17

The motion controller is one of the most fundamental modules in embodied intelligence systems. Driven by large-scale human motion-capture data and the motion-tracking paradigm, hum…

cs.RO2026

Unleashing Infinite Motion: Scaling Expressive Quadrupedal Motion via Generative Video Priors

Youzhi Liu, Li Gao, Yifei Qian +3

Quadruped robots have achieved remarkable locomotion, yet their behavioral repertoire remains confined to a few gaits--far from the expressive, companion-like presence long envisio…

cs.RO2026

Constraint-Aware Diffusion Priors for High-Fidelity and Versatile Quadruped Locomotion

Jianhui Chen, Ruixin Zhan, Liu Liu +2

Reinforcement learning combined with imitation learning has significantly advanced biomimetic quadrupedal locomotion. However, scaling these frameworks to massive, multi-source dat…

cs.RO2026

QuadFM: Foundational Text-Driven Quadruped Motion Dataset for Generation and Control

Li Gao, Fuzhi Yang, Jianhui Chen +4

Despite significant advances in quadrupedal robotics, a critical gap persists in foundational motion resources that holistically integrate diverse locomotion, emotionally expressiv…

cs.RO2026

ABot-N0: Technical Report on the VLA Foundation Model for Versatile Embodied Navigation

Zedong Chu, Shichao Xie, Xiaolong Wu +41

Embodied navigation has long been fragmented by task-specific architectures. We introduce ABot-N0, a unified Vision-Language-Action (VLA) foundation model that achieves a ``Grand U…

cs.RO2025

CE-Nav: Flow-Guided Reinforcement Refinement for Cross-Embodiment Local Navigation

Kai Yang, Tianlin Zhang, Zhengbo Wang +4

Generalizing local navigation policies across diverse robot morphologies is a critical challenge. Progress is often hindered by the need for costly and embodiment-specific data, th…