## 3 The Control Strategy of Two-Arm Cooperation Robot
### Simulation Experiments
#### 3.4.2 Simulation Experiments' Results  
In the experiment, the maximum number of training steps was set to 1 million. During the training process, the round ended immediately when the robot reached the target point, collided with an obstacle, exceeded the preset working range, or failed to reach the target point for a long time. Finally, the average reward at convergence was calculated. As can be seen in Figure 14, the reward obtained by the agent robot gradually increases, reaching a state of convergence at nearly \(5\times 10^{5}\) steps. The robot can mostly avoid obstacles to reach the target point of the collaborative manufacturing interrupter chamber within a short period of time. It is concluded that its chosen action can achieve better planning results and steadily control the robot arm to reach the target point. To test the success rate  
Figure 13: Two-arm cooperation robot in Unity environment. of reaching the target point, the following graph shows the success rate of the two arms reaching the key point of adjusting the interrupter chamber. As can be seen in Figure 15, the success rate of the two-arm cooperation robot at reaching the collaborative key point is increasing. The result proves that it has good stability for the collaborative manufacturing parts, and the success rate converges to about 96% when the number of steps is about times. It is a high success rate for the two-arm cooperation robot to reach the target point, proving that the algorithm can make the two-arm cooperation robot reach the target point accurately. After the training, the part grabbing test is carried out using the training result model, and the result is shown in Figure 16.  
As can be seen in Figure 16, the two-arm cooperation robot can eventually grasp the part successfully with no collision. It is proven that the algorithm is effective in commanding the two-arm cooperation robot to assemble parts. The robot will have a certain error relative to the ideal point position during the experiment. To verify whether the error present will affect the grasping, the error between it and the ideal point position is judged by observing the trajectory of the robot arm movement. The deviation curve of the trajectory variation of the two-arm cooperation robot over time is shown in Figure 17, which represents the deviation of the two-arm cooperation robot from the ideal target position in the x, y, and z directions. Figure 14: Convergence iteration curve during training. Figure 15: The success rate of the robot in completing the task. As can be seen in Figure 17, the deviation in the x direction is eventually controlled between \(-0.22\) m and \(-0.13\) m; the deviation in the y direction is eventually controlled between \(-0.05\) m and \(-0.02\) m; and the deviation in the z direction is eventually controlled between \(-0.15\) m and \(-0.09\) m as the time changes. The deviations in the x, y, and z directions are eventually within the manipulable range of the part manufacturing. The feasibility of the two-arm cooperation robot cooperation scheme is proved in this paper. To verify the effectiveness of the optimized method, the traditional method was compared  
Figure 16: Two-arm cooperation robots working together to grip parts. Figure 17: Deviation between actual position and ideal target position. with the method in this study. By comparing the time and success rate of grasping five parts, the results are shown in Table 2.  
For the arc extinguishing chamber part, compared with the traditional method, the optimized method assembly time is decreased by 2.88 s, the efficiency is increased by 44.17%, and the assembly accuracy is increased by 3.1%. For the magnetic system, the optimized method assembly time is decreased by 6.71 s, the efficiency is increased by 63.48%, and the assembly accuracy is increased by 3.6%. For the yoke part, the optimized method assembly time is decreased by 1.36 s, the efficiency is increased by 23.09%, and the assembly accuracy is increased by 2.2%.