IEEE Robotics & Automation Magazine - September 2012 - 64

MAX PLANCK INSTITUTE FOR BIOLOGICAL CYBERNETICS

Stabilization of the Teleoperation System
In both the cases of local and global intervention, it is necessary to consider the destabilizing effects (e.g., communication delay, packet loss, and sample and hold) arising
from the interconnection between the bilateral control
devices and the agent group.
The passive-set position modulation (PSPM) framework [22] can be used as a general tool for guaranteeing
master passivity and, therefore, stability of the closed-loop
teleoperation system when dealing with the aforementioned destabilizing effects by acting on the signals
exchanged over the communication channel. We omit
further details here and refer the interested reader to [16]
and [22] and references therein for a complete treatment
and formal proofs of these statements.
Another possibility is to use the two-layer approach
[23] that, enforcing passivity, guarantees a stable behavior.
Broadly speaking, this approach separates the exchange of
information between bilateral control devices and agents
into two layers. The passivity layer is controlled in such a
way that a passive energetic interconnection is established
between the bilateral control device and agents. In this
way, if the bilateral control device and agents are passive, a
stable behavior of the teleoperation system is guaranteed
independently of sampling, variable delays, and loss of

64

communication. The transparency layer determines the
inputs to be implemented on the bilateral control device
and agents to obtain the desired performance [e.g., (7)].
These desired inputs are then elaborated by the passivity
layer that, exploiting the energy exchanged between local
and remote sites, is able to implement them in a passivitypreserving way. For further details, the interested reader
can refer to [23] and [24].
QR-Based Experimental Test Bed
Hardware Setup

UAV Setup
We used QRs as UAVs because of their versatility, robustness, and construction simplicity. Furthermore, the QR
model perfectly matches our assumptions of the "UAV
Model and Overall Architecture" section, i.e., the ability to
track the reference quantities (pi , wi ) generated by the
FOTP owing to the flatness of the QR outputs (pBi , wBi ).
Our QR setup is a customized version of the MKQuadro (http://www.mikrokopter.de) open-source platform [see Figure 4(a)]. The QR frame spans 0:5 m, weighs
0:12 kg, and is made of four aluminum rods joined
together in a cross shape by two plastic center plates. Four
brushless Roxxy 2827-35 motors are
mounted at the end of each rod.
Each motor is driven via a pulsewidth modulation (PWM) signal by
Reflective Marker
a BL-Ctrl V2.0 brushless controller
Colored Marker
(BC) that can withstand an average
power consumption of 160 W and a
Monocular Camera
peak current of 40 A. A propeller of
0:254 m diameter is attached to each
μC Board
motor. By means of a custom-made
measure test bed using a Nano17
Motor
force/torque sensor (http://www.atiBC
ia.com/) [see Figure 4(b)], we found
that the maximum force and torque
are 9:0 N and 0:141 NÁm, respectively, and that the motor dynamics
Lipo
Battery
can be approximated by a first-order
Modular Frame
linear system with a time constant of
Q7 Board
0:047 s. For control design purposes,
Power Supply Board
this can be in first approximation
neglected with respect to the mechan(a)
ical dynamics of QR.
A 50-mm-square electronic board
is mounted in the middle of the
Force/Torque Sensor
frame and hosts a 8-b Atmega1284p
microcontroller (lC) clocked by a
20-MHz quartz. The lC can send the
desired motor speeds to the BCs by
(b)
means of an I2 C bus. The small board
also hosts 1) a three-dimensional (3Figure 4. (a) The QR setup with its parts and (b) the test bed is used for the
identification of the motor/propeller dynamics.
D) LIS344alh accelerometer with a
*

IEEE ROBOTICS & AUTOMATION MAGAZINE

*

SEPTEMBER 2012


http://www.mikrokopter.de http://www.ati http://www.ia.com

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