An Aviation Plug Regrasping Strategy Fused with Prior Knowledge Perception for Dual-Arm Collaborative Assembly Task

Assembly quality of typical electrical interfaces determines the safety of the aircraft, such as aviation plug. It is difficult to perform dexterous manipulation and assembly of randomly placed objects by the single-robot assembly method. To solve the above problems, an aviation plug regrasping strategy fused with prior knowledge perception for dual-arm collaborative assembly task is proposed in this paper. Firstly, the prior knowledge base of the assembly object is constructed based on the 3D point cloud model, and the transfer of prior knowledge is completed through a transfer matrix. Secondly, the recognition and pose estimation of randomly placed assembly object are realized based on the prior knowledge of the fusion SHOT features and the improved PCA algorithm. Then, based on the reachability and manipulability indices, the optimal transfer pose for the dual-arm robot is obtained, and the regrasping strategy of the dual-arm robot based on the motion transition graph is proposed to realize the regrasping manipulation of randomly placed assembly object. Finally, a dual-arm robotic system experimental platform is constructed to validate the proposed algorithms. Experimental results show that the proposed perception method is robust for randomly placed assembly object, and the regrasping strategy can adjust the pose of the assembly object before the final assembly task by the dual-arm robot.