Vision-based mobile robotic arm object gripping and handling.

In recent years, with the development of industrial robots and machine vision-related technologies, intelligent mobile robotic arms have been increasingly used in people's production lives. Object grasping and handling is the most typical application of mobile robotic arms in various production activities. Therefore, developing efficient, stable, accurate, and flexible mobile robotic arms to complete grasping and handling operations autonomously is vital. However, traditional robotic arms cannot be widely used in randomized and complex fields due to the limitations of their physical characteristics. This project aims to design a vision-based mobile robotic arm system with grasping and handling functions that can be used in complex fields and split into two parts: Simulation of the mobile robotic arm and training for the target recognition algorithm. In actual use, the object detection accuracy rate of 90% can be detected by the object accurately gripping and handling, suitable for high-volume industrial production of multiple types of material gripping and handling. [ABSTRACT FROM AUTHOR]