MANIPULATION
SeeTraceAct：基于跨本体演示视频的可见性感知潜在规划
Jaehyeon Son, Junhyun Kim, Kyle Kam, Jeremiah Coholich, Seok Joon Kim, Jinhoo Kim, Chris Dongjoo Kim, Jaemin Cho, Dieter Fox, Zsolt Kira
- 发表年份
- 2026
- 访问权限
- 开放获取
摘要
本文提出SeeTraceAct框架，通过可见性预测未来末端执行器轨迹，增强单次演示条件下的视觉-语言-动作模型的空间定位能力。实验表明，该方法在跨本体演示场景下显著优于基线，成功率提升12.5个百分点。
关键词
vision-language-actionone-shot learningcross-embodimentdemo-conditioned policyend-effector trace
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