Physical artificial intelligence

Physical artificial intelligence or physical AI refers to artificial intelligence (AI) systems that perceive, reason about and act within the physical world. These systems generally combine AI models with sensors, control systems, actuators and physical machines such as robots or autonomous vehicles. Physical AI overlaps with embodied artificial intelligence, robotics and autonomous systems, but it emphasizes the complete process of perceiving an environment, motion planning an action and physically executing the task to perform work. This differs from digital AI or generative AI (GenAI), which primarily stays in the information or digital realm.

The term became increasingly prominent during the AI boom in the 2020s as AI development expanded from primarily digital applications toward humanoid robots, self-driving vehicles, smart factories and other autonomous machines. Its boundaries are not standardized, and it is often treated as a continuation of earlier research in robotics and embodied intelligence rather than an entirely separate field.

Operation

Physical AI systems commonly operate through a continuous cycle of perception, planning and action. Cameras, lidar, radar, microphones and tactile or motion sensors collect information about the environment. Computer vision, machine vision, sensor fusion and simultaneous localization and mapping may be used to identify objects, estimate their positions and construct a representation of the surrounding world.

Open-source libraries such as OpenCV and Dlib provide computer-vision, image-processing and machine learning components that can be incorporated into perceptual systems.