This paper describes a general passivity-based framework for the control of flexible joint robots. Recent results on torque, position, as well as impedance control of flexible joint robots are summarized, and the relations between the individual contributions are highlighted. It is shown that an inner torque feedback loop can be incorporated into a passivity-based analysis by interpreting torque feedback in terms of shaping of the motor inertia. This result, which implicitly was already included in earlier work on torque and position control, can also be used for the design of impedance controllers. For impedance control, furthermore, potential energy shaping is of special interest. It is shown how, based only on the motor angles, a potential function can be designed which simultaneously incorporates gravity compensation and a desired Cartesian stiffness relation for the link angles. All the presented controllers were experimentally evaluated on DLR lightweight robots and their performance and robustness shown with respect to uncertain model parameters. Experimental results with position controllers as well as an impact experiment are presented briefly, and an overview of several applications is given in which the controllers have been applied.
The paper presents a new generation of torque-controlled lightweight robots (LWR) developed at the Institute of Robotics and Mechatronics of the German Aerospace Center. In order to act in unstructured environments and interact with humans, the robots have design features and control/software functionalities which distinguish them from classical robots, such as: load-to-weight ratio of 1:1, torque sensing in the joints, active vibration damping, sensitive collision detection, as well as compliant control on joint and Cartesian level. Due to the partially unknown properties of the environment, robustness of planning and control with respect to environmental variations is crucial. After briefly describing the main hardware features, the paper focuses on showing how joint torque sensing (as a main feature of the robot) is consequently used for achieving the above mentioned performance, safety, and robustness properties.
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