In this paper we use KUKA's Fast Robot Interface (FRI) to design and implement a tracking controller on the Lightweight Robot (LBR) IIWA. We seek low latency, accurate and smooth tracking of the link positions to facilitate human interaction tasks. Focusing on a single joint and its low-level series elastic dynamics, we identify the internal torque control structure and its characteristics. Tracking controllers of varying complexity are tested in an optical motion capture system to provide an independent external reference measurement. Using full state feedback of both motor position and sensed joint torque, we achieve smooth and good tracking of the unsensed link positions.

In this paper we examine joint torque tracking as well as estimation of external torques for the KUKA Lightweight Robot (LBR) IIWA. To support physical human-robot interaction tasks, we need smooth estimation that allows detection of delicate external events and good control to hide inertial forces. Unfortunately a transmission nonlinearity in the motor to joint gearing injects vibrations and limits the performance of the built-in torque controller and observer. We confirm the nonlinearity to be a spatially periodic deflection between the motor and joint. Identification of this behavior allows us to generate more accurate joint position measurements. We also design a matching spatial filter to remove the vibrations from joint torque measurements. Experiments on an LBR IIWA show that compensating for the nonlinearity provides smoother external torque estimates and improves the torque tracking performance. Furthermore, we are able to increase the gain margin more than three fold over the built-in controller.

In this paper, we present results from implementation of Levant's differentiator for velocity estimation from optical encoder readings. Levant's differentiator is a sliding mode control theory-based real-time differentiation algorithm proposed as a velocity estimator. The application of the technique allows stable implementation of higher stiffness virtual walls as compared to using the common finite difference method (FDM) cascaded with low-pass filters for velocity estimation. A single degree-of-freedom (DOF) linear haptic device is used as a test bed and an automated virtual wall hitting task is implemented to experimentally demonstrate that it is possible to extend the impedance-width (or Z-width) of a haptic interface via Levant's differentiator.