Chinese contentWholeBodyMem 为人形机器人引入记忆机制,突破 VLA 策略只看当下的局限
人形机器人转身走动就忘了刚才看到的东西,这篇用 SAM3 加关键帧记忆把真机成功率从 36.7% 拉到 88.3%,做机器人方向值得看看具体做法。
人形机器人转身走动就忘了刚才看到的东西,这篇用 SAM3 加关键帧记忆把真机成功率从 36.7% 拉到 88.3%,做机器人方向值得看看具体做法。
The notable shift is self-repair: instead of a fixed pipeline, the robot's manipulation code improves itself each time execution fails, so errors become training signal without human relabeling. Practitioners working on robot manipulation or agentic tool-building can study how error messages drive function patching in a physical loop. Compared with SAM2, pairing SAM3 with RGB-D gives this setup grounding in real 3D workspaces.
想让模型在不同参考图下都稳定分割?试试 CG-ICS,用概念推理代替简单视觉匹配,SAM3 和 MLLM 帮你搞定。