Robotics / Concepts and practice

Physical AI

Physical AI describes artificial intelligence that processes information about a physical environment and helps control robots or other physical systems.

Prepared by MALONI Robotics · Updated

How it works

Sensors supply observations, a model evaluates the situation, and a control system turns decisions into motion. Feedback supports adaptation. Simulation can support training and evaluation.

Where to start

For handling objects in changing positions, first specify the variation the robot must handle. Then compare a programmed solution with learned control against the same task.

Robot applications →

Limits and what to verify

The Physical AI label does not establish accuracy, safety or production readiness. Results from one research system cannot be assumed for an arbitrary catalogue robot.

Before requesting a quote

Collect examples of objects, lighting and failure situations. Measure task success, operator interventions and cycle time in a pilot. Separate the platform quotation from application development.

Related MALONI platforms

These links help you explore the portfolio. The technologies described are not automatically included in delivery.

Related concepts

Sources and further reading

MALONI offers robot platforms. This guide separates general principles, research examples and product offers; it is not an independent test of the linked models.

Your next project step

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