Dual-Arm Cooperative Transportation Based on Attitude Admittance Control

Dual-arm robotic systems are often required to perform tasks that involve dynamic interactions with their environment, such as grasping boxes, inserting components, or responding to external disturbances. In such systems, each manipulator may also exchange internal forces and torques with the other through the manipulated object, potentially leading to damage to the object or robot hardware. This paper proposes an admittance control strategy to improve internal force regulation during dual-arm cooperative manipulation. The method improves grasping performance and stability by adaptively responding to interaction forces. Furthermore, the RRT-Connect algorithm is used for grasp motion planning to ensure a reasonable force distribution during object transport. The proposed controller and planning method are validated through simulation experiments.