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Any2Any 助力人形机器人追踪模型高效迁移

作者 PulseAugur 编辑部 · [3 个来源] ·

研究人员开发了 Any2Any 方法，可高效地将全身追踪（WBT）模型迁移到新的人形机器人上。该方法显著减少了适应新机器人所需的数据和计算资源，从而能够更快地部署到不同的机器人平台。通过首先对齐运动学特性，然后微调对动力学敏感的模块，Any2Any 允许预训练模型被有效复用，仅用原训练成本的一小部分即可达到有竞争力的性能。 AI

影响 能够更快、更经济高效地将先进的人形机器人控制系统部署到新硬件上。

排序理由 该集群包含两篇研究论文，详细介绍了人形机器人控制和追踪的新方法和模型。

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →

Any2Any 助力人形机器人追踪模型高效迁移

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该集群包含两篇研究论文，详细介绍了人形机器人控制和追踪的新方法和模型。
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报道来源 [3]

  1. arXiv cs.AI TIER_1 English(EN) · Ming Yang, Tao Yu, Feng Li, Hua Chen ·

    Any2Any：人形机器人全身跟踪的高效跨体转移

    arXiv:2605.23733v1 Announce Type: cross Abstract: Whole-body tracking (WBT) models have become a key foundation for humanoid robots, enabling them to imitate diverse motions with high fidelity. Training such models from scratch requires large-scale data and computation, making ra…

  2. arXiv cs.AI TIER_1 English(EN) · Hua Chen ·

    Any2Any：人形机器人全身追踪的高效跨体迁移

    Whole-body tracking (WBT) models have become a key foundation for humanoid robots, enabling them to imitate diverse motions with high fidelity. Training such models from scratch requires large-scale data and computation, making rapid deployment on new humanoid platforms costly. T…

  3. arXiv cs.CV TIER_1 English(EN) · 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 X… ·

    SONIC：超大规模运动追踪，实现自然人形全身控制

    arXiv:2511.07820v3 Announce Type: replace-cross Abstract: Despite the rise of billion-parameter foundation models trained across thousands of GPUs, similar scaling gains have not been shown for humanoid control. Current neural controllers for humanoids remain modest in size, targ…

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