A multi-degree-of-freedom sorting control system based on the RBF-BP algorithm is designed to enhance the accurate sorting capability of robotic arm equipment. By utilizing the RBF-BP feedforward neural network, the motion trajectory of the robotic arm equipment is planned to achieve the modeling of the robotic arm’s motion trajectory based on the RBF-BP algorithm. Through transmission channels, sorting and Tool control instructions are fed back to the core control host, establishing a complete instruction execution loop. This, combined with the relevant hardware structure, results in the design of a multi-degree-of-freedom sorting control system for robotic arms based on the RBF-BP algorithm. Experimental results indicate that, with the same grasping capability, the system controlled by the RBF-BP algorithm successfully sorted 19 pieces of workpieces with a grabbing success rate of 95%, demonstrating that the designed system meets the original intention of enhancing the robotic arm’s accurate sorting capability.