Wang Xingxing on the Biggest Bottleneck of Physical AI: Alignment Between Models and the Physical World, Possibly Solvable in the Next 1 to 2 Years
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Wang Xingxing, founder of Unitree Robotics, said at the 9th Hongqiao International Economic Forum that the core challenge of physical AI today is the alignment between models and the physical world, and that related problems are expected to be solved in the next 1 to 2 years. He pointed out that multimodal large models already possess strong understanding, planning, and navigation capabilities, but when running on real robots, sensor measurements at the input end are inconsistent with the true state, and action commands at the output end do not match actual motion, with errors being particularly pronounced in contact-based tasks such as grasping and assembly. IDC data shows that in the first half of 2026, global humanoid robot shipments approached 25,000 units, a year-on-year increase of 432.1%, with shipments in the Chinese market exceeding 19,000 units, accounting for about 77.9% of the global total.
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王兴兴谈物理AI最大瓶颈，称未来1至2年或可解决凤凰网科技下载客户端 独家抢先看2026年11月05日 18:22:09 来自北京市
凤凰网科技讯 （编辑/宋淑美） 11月5日，在第九届虹桥国际经济论坛“人形机器人与具身智能产业创新发展合作”分论坛上，宇树科技创始人、董事长王兴兴表示，物理AI当前面临的核心挑战是模型与物理世界的对齐，相关问题未来1至2年有望得到解决。
王兴兴称，现阶段多模态大模型已经具备较强的理解、规划和导航能力，但在真实机器人上运行时，输入与输出仍会出现偏差。输入端存在传感器测量结果与真实状态不一致的问题，输出端则可能出现模型动作指令与机器人实际运动不匹配的情况。
这些误差在抓取、装配等接触类任务中尤为明显。机器人即使能够识别目标并规划动作，也可能因“最后几厘米”甚至“最后几毫米”的误差导致任务失败，进而影响模型的泛化能力和实际应用成功率。
此前，王兴兴曾表示，物理AI可能在未来1至2年或2至3年迎来实质性突破，宇树科技也在预研物理AI机器人自进化模型，希望通过模型自主采集数据、训练和迭代，减少机器人技能开发对人工编程及反复调试的依赖。
据IDC数据，2026年上半年全球人形机器人出货量接近2.5万台，同比增长432.1%；中国市场出货量超过1.9万台，占全球约77.9%。随着硬件出货规模扩大，模型与真实世界的对齐能力正成为机器人由演示走向规模化应用的关键环节。