Putting the Smarts into Robot Bodies

Previously, we have outlined three guiding principles for developing embodied artificial intelligence (EAI) systems.1 EAI systems should not depend on predefined, complex logic to handle specific scenarios. Instead, they must incorporate evolutionary learning mechanisms, enabling continuous adaptation to their operational environments. Additionally, the environment significantly influences not only physical behaviors but also cognitive structures. While the third principle focuses on simulation, the first two principles emphasize building EAI foundation models capable of learning from the EAI systems' operating environments. A common approach for EAI foundation models is to directly utilize pretrained large models.