Embodied AI Future: Robots Set to Merge Perception, World Models and Lifelong Learning

A STATERA Library series chapter outlines how next-generation embodied AI will combine advanced AI, robotics, world models, multimodal perception, autonomous decision-making and lifelong learning into one physical system. Unlike earlier robots that relied on fixed rules and controlled settings, these systems are expected to learn and adapt through continuous interaction with the real world. The piece argues that intelligence is inseparable from physical experience, with perception and action forming a continuous loop of observation, action and learning. It highlights large-scale world models that let robots predict outcomes before acting, along with vision-language-action models that can translate instructions directly into behavior. The material is presented in Korean as part of Volume 06 of the series on AMR AI and embodied intelligence.