Self-Calibration for an Object Integrative Handling System

The cooperative manipulation of rigid objects with multiple robotic arms leads to redundant actuation, which is a challenging configuration for the robot control. The object is connected to multiple robotic arms and integrated into the kinematic structure, resulting in a Re-Configuration for each handling task. A recent example of this object integration is the investigated PARARIP handling system. Inaccuracies of the robotic arms and tolerances of the object lead to deviations of the grasp points at the object and inadequate object positioning. Today's control and calibration approaches, however, do not target the identification of the uncertain grasp points. Accordingly, a self-calibration procedure for the object integrative handling system is developed to identify the actual grasp points at the object. It is based on the combination of direct and inverse kinematic calculations. The aim of the paper is to evaluate redundant sensor-information of cooperating robotic arms to identify the actual grasp points at the integrated object, to increase the system accuracy and to limit the impact of the coupling effects. The sensitivity and influencing factors of the method were investigated and verified in simulations. The results show that the available redundant sensor information for object integrative robots or handling systems can be used to identify the grasp points at the object and compensate the internal inaccuracies automatically.