There are different possibilities for teleoperation. One of the most common is the use of kinesthetic feedback, resulting from the interaction forces between the slave robot and the remote environment, provided to the master to be able to perform a task remotely.
However, in an uncertain environment caution needs to be taken, since a robot system with high stiffness and high force can do some serious damage. Furthermore, a robot system with a low stiffness might not be able to realize the desired force. The stiffness of the robot system determines our interaction possibilities. Therefore, by changing the stiffness the way of interacting can be changed. The interaction performance of the human arm turns out to be very effective, due to the ability to change the arm dynamics. Changes in arm dynamics are due to the regulation of the endpoint impedance caused by muscular coactivations and body posture. With co-contraction of the arm muscles, the endpoint impedance can be regulated without changing the arm configuration. Because of the effectiveness of the human arm in these environments, it is desired that the robot arm behaves in a similar way. Therefore, the properties causing this effectiveness should be transferred to the robotic system.
From the work of [1] it follows that this can be achieved by combining position trajectories with certain stiffness profiles. These stiffness profiles can be derived from EMG measurements in the muscles of the human arm and transferred to the robotic arm in real-time.
This method extends the work done by [2], by analyzing all the contributing muscles to the endpoint stiffness with surface EMG and combining the position trajectories with certain stiffness profiles. In the work of [2] the end-effector stiffness scales with an estimate of the co-contraction around the elbow of the teleoperator. To reduce the negative effects of time delays within the work of [2] the work of [3] followed (Bi-directional Impedance Reflection).
This work extends the reflection of the human arm impedance to the robot arm by reflecting the impedance of the robot arm to the operator as well. To compensate for the delayed motion a prediction of the trajectory is made.
To see whether the new method, based on [1] and combined with Bidirectional Impedance Reflection, improves upon the Bi-directional Impedance Reflection controller of [3] a comparative study will be done.
[1] A. Ajoudani et al. (2012). Tele-Impedance: Towards Transferring Human Impedance Regulation Skills to Robots. The University of Pisa.
[2] K.J. van Teeffelen et al.(2018). Intuitive Impedance Modulation in Haptic Control using Electromyography. The University of Twente.
[3] R.J. Lieftink et al. (2020). Bi-directional impedance reflection for Cartesian space telemanipulation control to reduce the effect of time delay. The University of Twente.
Human Impedance regulation in Haptic Control using Electromyography combined with the posture of the human arm to increase transparency within telemanipulation control
Finished: 2021-07-19
MSc assignment