Example

Some other use cases for combining RAG and YOLO include: 1. Visual Perception (YOLO): The robot uses YOLO (You Only Look Once), a quick object detection system, to analyze video from its camera. YOLO swiftly identifies and labels items in view, such as people, furniture, obstacles, or specific tools and products. 2. Contextual Understanding (RAG): The identified objects trigger a Retrieval Augmented Generation (RAG) system. RAG pulls information from a knowledge base regarding the objects, their features, and interaction methods. This could include: - Structured Data: Information from databases about object specs, usage instructions, and safety info. - Unstructured Text: Articles, manuals, or discussions on how people interact with these objects. - Real-time Sensor Data: Extra data from the robot's sensors (like distance or temperature) to give context. 3. Decision Making & Action: RAG uses the gathered info and the current context (like the robot's goal and surroundings) to create a response. This might include: - Navigation Instructions: If YOLO spots an obstacle, RAG might tell the robot how to navigate around it. - Interaction Commands: If YOLO sees a tool, RAG could provide steps on how to pick it up or use it. 4. Information Gathering: If YOLO recognizes an unfamiliar object, RAG could prompt the robot to ask a human for more information.