The paper presents BRIDGE, an open‑source 88 cm tall humanoid robot designed through a data‑driven morphology‑control co‑design framework that aligns robot shape with human‑like movement. It introduces a new metric combining kinematic retargeting fidelity and dynamic tracking performance to evaluate morphological fidelity, achieving state‑of‑the‑art results against baseline humanoids. The released platform, along with its control policy, demonstrates superior human motion capture, robust balance, and dynamic maneuvers, with supporting videos and code available online.
arXiv:2510. 08807v2 Announce Type: replace-cross Abstract: From loco-motion to dextrous manipulation, humanoid robots have made remarkable strides in demonstrating complex full-body capabilities.
By Zhenyu Zhao, Hongyi Jing, Xiawei Liu, Jiageng Mao, Abha Jha, Hanwen Yang, Rong Xue, Sergey Zakharov, Vitor Guizilini, Yue Wang
arXiv:2511. 07820v4 Announce Type: replace-cross Abstract: Despite the rise of billion-parameter foundation models trained across thousands of graphical processing units (GPUs), similar scaling gains have not been shown for humanoid control.
By Zhengyi Luo, Ye Yuan, Tingwu Wang, Chenran Li, Fernando Casta\~neda, Sirui Chen, Zi-Ang Cao, Jiefeng Li, David Minor, Qingwei Ben, Jinhyung Park, David Sami, Zi Wang, Xingye Da, Runyu Ding, Cyrus Hogg, Lina Song, Edy Lim, Eugene Jeong, Tairan He, Haoru Xue, Wenli Xiao, Simon Yuen, Jan Kautz, Yan Chang, Umar Iqbal, Linxi "Jim" Fan, Yuke Zhu
arXiv:2606. 19935v1 Announce Type: new Abstract: Humanoid robots require co-speech motions that are not only expressive and speech-aligned, but also physically executable under embodiment constraints.
By Zhangzhao Liang, Xiaofen Xing, Mingyue Yang, Wenlve Zhou, Xiangmin Xu
arXiv:2509. 15443v2 Announce Type: replace-cross Abstract: Human-to-humanoid imitation learning presents a promising pathway to address the severe data scarcity bottleneck in robotics by utilizing abundant, large-scale human motion collections.
By Xingyu Chen, Hanyu Wu, Sikai Wu, Mingliang Zhou, Diyun Xiang, Haodong Zhang, Yangchen Zhou, Yukang Gao, Yi Gu, Renjing Xu
arXiv:2605. 23733v2 Announce Type: replace-cross Abstract: Whole-body tracking (WBT) models have become a key foundation for humanoid robots, enabling them to imitate diverse motions with high fidelity.
By Ming Yang, Tao Yu, Feng Li, Hua Chen