FieldAI expanding into multimodal robot control

This pushes FieldAI from being a mobility layer into being a full robot operating layer for work that mixes moving, seeing, and handling objects. Navigation gets a robot to the right shelf or machine. Manipulation and multimodal control let it pick a part, use a tool, inspect with cameras and sensors, and finish the job. That expands FieldAI from inspection and site scanning into factory cells, warehouse picking, and other workflows where customers pay for completed tasks, not just autonomous movement.

• FieldAI already runs as a hardware agnostic control stack on legged, wheeled, flying, and tracked robots, with on device inference and a sensor fusion model using cameras, LiDAR, radar, and IMU. Adding arms and end effectors is a logical next step because the same stack already handles perception, planning, and safety in messy industrial sites.
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• The closest software comparison is Skild AI, which exposes grasping, handover, and navigation through an API on mobile manipulation platforms. Physical Intelligence is pursuing the same broad control thesis, with models trained across multiple robot types and dozens of manipulation tasks. The market is moving toward foundation models that control whole workflows, not single robot subsystems.
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• Once FieldAI ships software only SDKs, simulation tools, and OEM licensing, revenue can shift from one off payload integrations toward recurring software. That matters because robot makers and factory integrators often already own the hardware. They need the intelligence layer that lets an existing base, arm, or inspection robot do a new job without rebuilding the whole machine.
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The next phase of robotics value will accrue to the companies that turn robot intelligence into a reusable software layer across many bodies and many tasks. If FieldAI executes, it can move from selling autonomy for niche field deployments to becoming embedded infrastructure for OEMs, integrators, and industrial operators building mobile manipulation systems at scale.