2026之江营商论坛观察：制度型开放里的“四篇文章”

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2026之江营商论坛观察：制度型开放里的“四篇文章”

装箱机器人把堆垛稳定性纳入每一步选择

新箱子会陆续到达，机器人摆放眼前的箱子时，既不清楚以后还有什么形状，也不能让已经堆好的箱子倒下。SHORE方法同时估计某个位置能否放稳，以及在放稳的条件下这一动作能带来多少收益，再决定挑哪只箱子、如何转向以及放在哪里。训练使用了实际执行结果和模拟的其他选择，部署时不需要为每一步新增搜索。 Chang Shi和Ann Majewicz Fey的这项研究收录在11月6日更新的计算机科学预印本列表中。

在Isaac Gym仿真中，该方法约用40万步达到73%的空间利用率，不建模稳定性的同类学习器约需100万步。在包含60种箱子的测试中，利用率为73.4%，对照方法为58.8%。与此同时，放置失败频率也从对照组的0.63%升至1.03%。作者另外做了真机演示。这组数据给出了装得更多与失稳风险上升之间的实际取舍。

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