most citedFALCON: Learning Force-Adaptive Humanoid Loco-Manipulation

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cs.RO2026

Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models

Yifu Yuan, Yaoting Huang, Xianze Yao +20

We introduce Embodied-R1.5, a unified Embodied Foundation Model (EFM) that integrates comprehensive embodied reasoning capabilities, spanning embodied cognition, task planning, cor…

cs.RO2026

RIO: Flexible Real-Time Robot I/O for Cross-Embodiment Robot Learning

Pablo Ortega-Kral, Eliot Xing, Arthur Bucker +13

Despite recent efforts to collect multi-task, multi-embodiment datasets, to design recipes for training Vision-Language-Action models (VLAs), and to showcase these models on differ…

cs.RO2026

ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching

Shuoheng Zhang, Yifu Yuan, Hongyao Tang +7

Existing imitation learning methods enable robots to interact autonomously with the physical environment. However, contact-rich manipulation tasks remain a significant challenge du…

cs.RO2026

RPL: Learning Robust Humanoid Perceptive Locomotion on Challenging Terrains

Yuanhang Zhang, Younggyo Seo, Juyue Chen +7

Humanoid perceptive locomotion has made significant progress and shows great promise, yet achieving robust multi-directional locomotion on complex terrains remains underexplored. T…

cs.RO2025★ 1 cited

FALCON: Learning Force-Adaptive Humanoid Loco-Manipulation

Yuanhang Zhang, Yifu Yuan, Prajwal Gurunath +7

Humanoid loco-manipulation holds transformative potential for daily service and industrial tasks, yet achieving precise, robust whole-body control with 3D end-effector force intera…