Hierarchical robustness approach for nonprehensile catching of rigid objects

Catching is one of the most complex tasks in the area of dynamic manipulation. Exact information on the position and orientation of a rigid object is crucial in order to accomplish manipulation tasks. Both motion planner and control strategy use these data to achieve the desired contact of a predefined surface with a nonprehensile end-effector, e.g. flat plate. This paper presents a multi-level approach for robust task planning and execution for planar catching of rigid bodies. On the top level the choice of the best catching strategy is made. Different catching actions are introduced and classified based on relative translational and rotational velocities between the end-effector and the object. A motion planner is implemented on the middle level that produces smooth motion trajectories depending on the chosen strategy. Yet, some uncertainties occur during task execution due to sensory data, trajectory tracking and unmodeled dynamics. Therefore, a robust tracking control is implemented on the bottom level to guarantee task execution in presence of uncertainty in robot parameters. A sustainable framework is being used taking the dynamics of the robot, the object and the environment into account to create a consistent and versatile catching system.