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清华推出开源具身智能框架:用VLM解决机器人动作异构一致性难题 ...
三是 轻量化架构 ,UniAct-0.5B模型仅用0.5亿参数,即在对现实与模拟机器人任务的测试中超越14亿参数的OpenVLA,验证了通用动作的高效性。 此外,高效的异构解码机制让UniAct具备了 可直接快速部署的通用动作 ,为控制具身智能体提供了新的方式,通过从码本中直接挑选通用动作即可控制不同具身智能体完成指定的任务,play with code!
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