Design and Research of Indoor Distribution Robot Based on YOLOv8 Network

With the rapid development of modern logistics and intelligent warehousing technologies, the application of indoor delivery robots has been increasing. However, current indoor delivery robots still face significant challenges in areas such as motion performance, operational efficiency, space utilization, compatibility for item placement, and intelligent route planning and obstacle avoidance capabilities. To address these issues, this paper proposes a solution for an indoor delivery robot based on the YOLOv8 network. The solution uses ROS (Robot Operating System) as the software control platform, with YOLOv8 as the core module for intelligent driving, and combines the A* algorithm for global path planning. This enhances the robot's intelligence in target recognition, path planning, and obstacle avoidance. The robot's design covers the overall planning of mechanical structures and functional modules, and its key functionalities are validated through simulation experiments. The results show that the designed robot can quickly identify obstacles, accurately plan paths, and efficiently execute delivery tasks, offering significant advantages in optimizing warehouse space utilization and reducing energy consumption. Additionally, the robot's enhanced obstacle and traffic sign recognition capabilities, improved by the SE attention mechanism in YOLOv8, further contribute to its performance.