AI Vision + AI Robot convergence · Perceive → Decide → Act
AI-driven seeing and judging is now unmanned, but action is still taught by people. Now, given only the goal, the robot decides where and how to work — and executes.
Vision alone only sees; robots alone have no eyes. Manufacturing innovation is complete only when perception and action are connected.
Even when AI perceives the situation, the action after the decision still depends on people and robot teaching.
Moving only by taught rules — every product or process change means a person has to teach it all over again.
Perceive → Decide → Act → Automatic feedback. Shifting from Human-in-the-loop to Machine-in-the-loop.
On a hot-stamped (PHS) automotive body-part line, AI vision recognizes parts on the conveyor and the loading cart, and two cobots calculate loading positions that fit the cart on their own. When the product changes, you only enter its dimensions.
Rows and loading positions are calculated from the cart size and product dimensions, greatly reducing re-teaching for each product.
Evolving from today's integrated system (V1.5) to teaching-less operation that decides its own methods (V2.0).
The core technology axis for moving from perception to autonomous action.
Rapidly transfers capabilities learned in one process to new products and processes. (Domain Adaptation)
Robots learn refined motions on their own by imitating skilled workers.
Work result data cycles back into MLOps automatically, continuously improving the next operation.
Having operated AI Vision on the factory floor for 10 years and built MLOps ourselves, we can finally connect judgment and action.
Frequently asked questions about Physical AI.
We'll show you how Physical AI can be applied to your process, with real-world case studies.
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Share 3–5 photos of the part and your process conditions (takt time, defect types). Our engineers will review feasibility and the right approach for AI vision or robotics and get back to you.
