IEEE Robotics & Automation Magazine - December 2015 - 107

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Conclusions and Future Work
This article highlights the features of JOpenShowVar as a
cross-platform communication interface to Kuka industrial

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Effectiveness
Concerning the fourth case study, the aim is to show the possibility of operating the robot and transferring the corresponding force feedback to the operator. The plots in
Figure 14(a) and (b) show the actual position for the x-, y-,
and z-axes as a result of the haptic input device's movements,
operated by the user, and the corresponding joint angles, respectively. In this particular case, the operator maneuvers the
robot to lift the end-effector up at first, then down again with
a displacement also in the x- and y-axes. In this case study,
the input signal is not scaled to the robot's workspace, since
the haptic device is only used to set the direction of movement for the robot and to transfer the corresponding force
feedback to the operator. Even though there is a delay between the input signal and the actual position, the results
show that the system is quite responsive to the user's inputs.
Figure 14(c) and (d) shows the torques applied to the robot's
joints and the corresponding forces applied to the robot's
end-effector, respectively. The operator also perceives a force
feedback that is proportional to forces applied to the robot's
end-effector.

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Delay (ms)

data. Using data structures it is possible to simultaneously access several variables, thereby minimizing the access time.
Considering the third case study, a time-delay analysis
is carried out for the same Cartesian paths, as shown in
Figure 12. Even though there are a few spikes with a larger
time interval, an average access time of 4.27 ms is obtained in this case. It should be noted that all of the considered case studies are equally affected by similar
communication delays except for the second case study
which is performed offline and, therefore, does not present any run-time delays.
To further assess the performances of the proposed interface with regard to the communication delay, an additional
experiment is performed. In particular, the possibility of developing alternative control methods is considered (as presented in case study 3). Any custom control algorithm that
does not use the standard KRC kinematics must calculate the
corresponding sampling point configurations for the desired
end-effector positions. In other words, each control algorithm works as a motion planner. To ensure smooth movements for the manipulators, it is necessary to generate
trajectories out of these given sampling points. A well-suited
trajectory is the basic prerequisite for the design of a highperformance tracking controller and ensures that no kinematic nor dynamic limits are exceeded. Such a controller
guarantees that the controlled robot will follow its specified
path without drifting away. Therefore, feedback control has
to be applied to be able to compensate external disturbances
as well as disturbances from communication time delays.
Note that time data are a free parameter because, as already
mentioned, the sampling time of the mapping algorithm is
not constant. A possible solution for generating well-suited
trajectories consists of using a proportional integral derivative (PID) controller for each joint. Different methods can be
used to tune the PID parameters, such as the one proposed
in [14]. The response of the PID controller that is adopted in
the third case study is shown in Figure 13 for all joints of the
robot. The interface provided by JOpenShowVar demonstrates a relatively fast reaction to the inputs and reasonable
output error for research purposes, considering the dimension of the controlled model.

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Time (s)

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Figure 12. Case study 3: time-delay analysis for the corresponding
Cartesian paths shown in Figure 11.

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Figure 13. Target and response of the adopted PID controller for
all the joints of the robot.

DECEMBER 2015

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IEEE ROBOTICS & AUTOMATION MAGAZINE

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107



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