The use of AI with cognitive technologies is dramatically reshaping the field of making intelligent machines. In this paper, we developed a framework using deep learning to help robots with perception, memory, attention, reasoning and making decisions. Applying information from neuroscience and cognitive psychology, we design our model by using Vision Transformers (ViT) for vision tasks, Recurrent Neural Networks (RNN) to represent memory, attention mechanisms for studying focus and language models that generate output. This work establishes the foundation for agents that can move through their surroundings as humans do and respond carefully to what is happening. The suggested framework is a step towards creating AI systems that function openly, are strong and process information similarly to human minds in real-world scenarios.