第一是泛化：料箱颜色、尺寸、新旧程度都不同，能不能用同一个模型稳定完成识别、抓取与搬运。第二是导航：搬起之后从A点到B点怎么走，路径规划、避障，途中被打断后能不能续做。第三是策略理解：比如“从面前100个箱子里搬走50个”，机器人能不能理解数量、以及该选择哪50个箱子，到目的地怎么码放，以及放下后要不要把物体取出等等，每个环节都存在问题。
Testing was conducted by Apple in January and February 2026 using preproduction 16-inch MacBook Pro systems with Apple M5 Max, 18-core CPU, 40-core GPU, 128GB of unified memory, and an 8TB SSD. Tested with FIO 3.41, 1024KB request size, 10GB test file and IO depth=8. Performance tests are conducted using specific computer systems and reflect the approximate performance of MacBook Pro.
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