The symbol grounding problem is a well-known philosophical problem, e.g., a person with no related knowledge of the Chinese language attempts to learn it via a Chinese-Chinese dictionary. However, in the engineering of AGI (Artificial General Intelligence) systems, grounding becomes essential for interacting with a real-world environment. For example, obtaining a food item from a person’s cupboard requires an understanding and interaction with the environment which an ungrounded symbolic AGI may not possess. Grounding an AGI system or Brain-Inspired Cognitive Architecture (BICA) via mobile robotics is described. The PetitCat project includes an open-source software interface between the Python code of an AGI project and a mobile robotics device. The interface allows real-time communication between the Python code on a desktop or server via wireless network to the lower-level C/C++ code used to control a robotic device. The PetitCat project is targeted at studying symbol grounding and autonomous bottom-up interactive learning in the framework of theories of enaction, active inference, predictive coding, and developmental and constructivist learning.