Projected Force-Admittance Control for Compliant Bimanual Tasks

Bimanual manipulation is fundamental for humanoid robots. It has gained a lot of attention in robotics research as a key ability towards versatile behavior. To achieve such behaviors in real-world tasks, bimanual controllers must be stable and simple to implement. On the other hand, admittance and impedance control frameworks are well-known for their efficiency in robot's manipulation tasks which require compliant motions e. g. for physical human-robot interactions. Based on these frameworks, we propose a new control framework, the Projected Force-Admittance Control (PFAC), for compliant bimanual manipulation tasks. By analyzing the load distribution in bimanual tasks using grasp mapping technique, the controller uses the projected constraint force, which, together with the actuation force given by the PI controller, are fed into an admittance control framework, and finally provides the virtual target pose to an impedance controller that can be modeled as a mass-spring-damper system. With this control strategy, we ensure motion synchronization and target force regulation under external perturbations and/or while tracking a trajectory. We demonstrate the stability and usability of the controller in several experiments with the humanoids robot ARMAR-6. Combining it with movement primitives approaches such as Dynamic Movement Primitive (DMP), a variety of compliant bimanual tasks are implemented and evaluated.