Prioritized Hierarchical Compliance Control for Dual-Arm Robot Stable Clamping
This work addresses safety and stability issues in human-robot collaboration for clamping tasks, but it is incremental as it builds on existing compliance control and hierarchical optimization techniques.
The paper tackles the problem of dual-arm robot clamping failure due to incidental disturbances from the environment or humans, proposing a prioritized hierarchical compliance control method that enables stable clamping and compliance against disturbances, as verified on a 14-DOF robot.
When a dual-arm robot clamps a rigid object in an environment for human beings, the environment or the collaborating human will impose incidental disturbance on the operated object or the robot arm, leading to clamping failure, damaging the robot even hurting the human. This research proposes a prioritized hierarchical compliance control to simultaneously deal with the two types of disturbances in the dual-arm robot clamping. First, we use hierarchical quadratic programming (HQP) to solve the robot inverse kinematics under the joint constraints and prioritize the compliance for the disturbance on the object over that on the robot arm. Second, we estimate the disturbance forces throughout the momentum observer with the F/T sensors and adopt admittance control to realize the compliances. Finally, we perform the verify experiments on a 14-DOF position-controlled dual-arm robot WalkerX, clamping a rigid object stably while realizing the compliance against the disturbances.