LEARNING
Any2Any: 面向人形全身跟踪的高效跨本体迁移
Ming Yang, Tao Yu, Feng Li, Hua Chen
- 发表年份
- 2026
- 访问权限
- 开放获取
摘要
本文提出Any2Any范式,通过运动学对齐和轻量级参数高效微调,将预训练的全身跟踪模型高效迁移到新的人形机器人平台上。实验表明,仅需1%的数据和计算量即可实现与从头训练相当甚至更优的跟踪性能。
关键词
whole-body trackingcross-embodiment transferparameter-efficient fine-tuninghumanoid robotskinematic alignment
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