Enhancing the reliability of mobile robots control process via reverse validation

Abstract

The article deals with integrating the inertial navigation unit implemented into the system of controlling the robot. It analyses the dynamic properties of the sensors of the inertial unit, for example, gyroscopes and accelerometers. The implementation of the original system of controlling the mobile robot on the basis of autonomous navigation systems is a dominant part of the article. The integration of navigational information represents the actual issue of reaching higher accuracy of required navigational parameters using more or less accurate navigation systems. The inertial navigation is the navigation based on uninterrupted evaluation of the position of a navigated object by utilizing the sensors that are sensitive to motion, that is, gyroscopes and accelerometers, which are regarded as primary inertial sensors or other sensors located on the navigated object.

Full text

Research Article
Enhancing the reliability of mobile
robots control process via
reverse validation
Yuri Turygin
1
, Pavol Boz
ˇek
2
, Yuri Nikitin
1
, Ella Sosnovich
3
,
and Andrey Abramov
1
Abstract
The article deals with integrating the inertial navigation unit implemented into the system of controlling the robot. It
analyses the dynamic properties of the sensors of the inertial unit, for example, gyroscopes and accelerometers. The
implementation of the original system of controlling the mobile robot on the basis of autonomous navigation systems is a
dominant part of the article. The integration of navigational information represents the actual issue of reaching higher
accuracy of required navigational parameters using more or less accurate navigation systems. The inertial navigation is the
navigation based on uninterrupted evaluation of the position of a navigated object by utilizing the sensors that are sensitive
to motion, that is, gyroscopes and accelerometers, which are regarded as primary inertial sensors or other sensors
located on the navigated object.
Keywords
Controlling, inertial navigation system, reverse validation, mobile robot
Date received: 5 May 2016; accepted: 6 July 2016
Topic: Special Issue - Manipulators and Mobile Robots
Topic Editor: Tomas Brezina
Introduction
The word ‘inertial’ comes from the original word ‘inertia’,
which means inertia and inability of motion. The principle
of inertial navigation obeys the laws of classical
mechanics defined by Newton. The inertial navigation
system (INS) includes at least one navigation computer
and a platform or a module containing accelerometers and
gyroscopes.
1,2
From the constructional point of view,
inertial navigation systems are divided into platform so-
called gimballed systems and non-platform so-called
strapdown systems. In the platform system, inertial sen-
sors are attached to the platform that is installed in a
gimbals suspension with three degrees of freedom with
the aim of remaining the constant space orientation in
defined directions (north–south, east–west and vertically
on performing the gravitational attraction), while the gim-
bals suspension is firmly connectedtotheconstructionof
the navigated object. The moving mechanical parts of the
systems cause
3
relatively low reliability towards the non-
platform systems. The inertial sensors of non-platform
systems are firmly connected to the construction of the
object (usually in the centre), for whose navigation they
are determined.
1
Kalashnikov Izhevsk State Technical University, Izhevsk, Russia
2
Slovak University of Technology in Bratislava, Faculty of Materials
Science and Technology in Trnava, Slovakia
3
Kalashnikov Izhevsk State Technical University, Izhevsk, Russia
Corresponding author:
Yuri Turygin, Izhevsk State Technical University of the Name M.T.
Kalashnikov, 7 Studencheskaya Street, Izhevsk 426069, Russian
Federation.
Email: turygin@istu.ru
International Journal of Ad vanced
Robotic Systems
November-December 2016: 1–8
ªThe Author(s) 2016
DOI: 10.1177/1729881416680521
journals.sagepub.com/home/arx
Creative Commons CC-BY: This article is distributed under the terms of the Creative Commons Attribution 3.0 License
(http://www.creativecommons.org/licenses/by/3.0/) which permits any use, reproduction and distribution of the work without
further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/
open-access-at-sage).

Both types of the inertial navigation systems consist of
an inertial measurement unit (IMU) and a navigation com-
puter. The IMU is an underlying element of each INS.
Sensors whose output is influenced only by the motion of
the object, on which the IMU is placed, are regarded as
primary sensors of the IMU. Sensors of angular velocity
whose output signals after integrating are used for deter-
mining the orientation in space, and accelerometers whose
output signals after precise compensating the gravitational
acceleration and Coriolis force can be integrated for speed
and position are the primary sensors in the inertial naviga-
tion.
4
Such an IMU has six degrees of freedom, which
means that it enables measuring the translational and rotary
motion in three orthogonal axes.
In the autonomous navigation, the accuracy of inertial
sensors plays a key role. The errors of current inertial sensors
have the value of approximately 0.01/h for gyroscopes and
100 mg for accelerometers. The mentioned errors are inte-
grated in time and cause an error of determining the position
that is expressed by non-accuracy of measuring per hour,
which is, however, minimal. Such high-powered IMUs are
implemented only into the inertial navigation systems for a
special use where the highest possible accuracy is required.
In less demanding applications, more affordable IMUs are
used. Their lower accuracy is compensated by implementing
into the integrated navigation systems in which the required
accuracy is achieved by integrating the navigation informa-
tion from more navigation systems. The ADIS16365 inertial
sensor,
2,5
which has been produced since 2009, belongs to
the novelty in the sphere of such IMUs. The ancestor of this
sensor (ADIS16350) was awarded in the Best of Sensors
Expo 2007.
The ADIS163 xx inertial sensor is determined for the
applications of guidance, control and stabilization of the
body with six degrees of freedom in space. The sensor
can be used for controlling and an analysis of motion,
navigation and stabilization of the body or an image in
different applications. As a part of the integrated navi-
gation system, it is suitable for using in the area of
robotics for the navigation and control of autonomous
mobile robots. The software for controlling the auto-
matic calibration of the system error, sampling, digital
filtration, the internal test of sensors, feeding, monitor-
ing the state of the sensor and the additional digital I/O
port is implemented into sensor circuits.
6,7
From a structural point of view, inertial navigation
systems are divided into platform (cardan INS) and
non-platform systems (strapdown systems). In platform
systems, inertial sensors are mounted on a platform
installed in a cardan gimbal with three degrees of freedom,
in order to keep a constant space orientation in predefined
directions (north–south, east–west and perpendicular to the
earth’s gravity effect), while the gimbal is fixed to the
structure of the navigated object. Movable mechanical
parts of these systems cause relatively low reliability com-
pared to non-platform systems. In non-platform systems,
inertial sensors are firmly attached to the structure of the
object, the navigation of which they are determined for.
Both types consist of an INS IMU and a navigational com-
puter, as illustrated in Figure 1.
A navigation computer is the core of the inertial naviga-
tion system. The navigation computer processes the mea-
sured data from the IMU and generates information about
the angular position, the velocity and the position of the
navigated object based on the known initial conditions. The
measured data from the gyroscopes represent the angular
velocity vector of the navigated object regarding the inertial
coordinate system marked with the index ‘i’andmeasuredin
individual axes of Cartesian coordinate system of the navi-
gated object marked with the index ‘b’ (b stands for body)
Figure 1. Block diagram of the INS working in the navigation coordinate system.
2International Journal of Advanced Robotic Systems

!b¼½!bx;!
by;!
bz(1)
By application of more mathematical modifications and
integration of the angular velocity, the information about the
position of the navigated object in regard to the reference
system is attained (direction, tilt, inclination, respectively
transformation matrix or quaternions). The data measured
by the three-component accelerometer represent the vector
of acceleration measured in the axes of the navigated object
ab¼½abx;aby ;abz(2)
After the initial data processing, the data are transformed
into the reference system. Then, compensation of gravity
and Coriolis acceleration is carried out, followed by dual
integration. The first integration offers information about the
velocity of the navigated object in the reference system,
while the second integration provides information about the
object location. Although a navigation computer seems to be
based on a simple principle, it actually comprises nine dif-
ferential equations, respectively, and three differential equa-
tions in vector shape (form). However, these equations are
not required to be stated in this contribution.
The implementation of an inertial system
into the system of controlling a mobile
robot
In contemporary space demands and the effective utilization
of space, the mobile robot is forced to work in confined
conditions, and the motion of a tool or the manipulation with
parts requires surgical accuracy. This gives considerable
demands for the right calibration of the robotic device.
8
The accuracy of the mobile robot is characterized first and
foremost by the size of the deflections of its effector on the
working arm from the specified position. So far, it has been
possible todetermine the trajectory of the arm or the working
tool of the mobile robot during the motion in space only by
photogrammetric methods.
9
Ensuring higher accuracy is
enabled by geodetic methods. However, they require the arm
of the mobile robot to be at rest. Determining the position of
the arm in space with required accuracy even if the arm is
moving is enabled by inertial measuring systems.
10
In prin-
ciple, it is determining the trajectory of the controlled point of
the arm, while the task is solved in the conditions character-
istic just for the control of industrial mobile robots.
The principle of inertial determining the position embo-
dies in constant processing the information flow about the
motion of the object, that is, continual measuring the vector
of instantaneous acceleration and slewing. It is measured in
a coordinate system
11
defined by the construction of mea-
suring system, so it must be transformed to such a system in
which determining the position or trajectory is required.
The information needed for transformation can mostly be
obtained from gyroscopic measuring. In rare cases,
non-requiring high accuracy in determining the position
or in very small values rotations of the system is relatively
expensive, and sensitive gyroscopes are replaced by sen-
sors of angular acceleration or power.
The structure of mobile robots is not unified. There are a
lot of conceptual and constructional solutions of robots
resulting from the expected utilization. A robotic system can
be divided into a mechanical and control subsystem irrespec-
tive of their solution. The motion of working organs of a
mobile robot is provided by mechanical parts. The activity of
all the parts of the mobile robot and programming of its
expected activity are enabled by the control subsystem.
The mobile robot or its part (gripper and arm) has to
meet the requirement of three degrees of freedom of motion
in the X-axis, Y-axis and Z-axis at a minimum to achieve a
random point in space. The next three degrees of freedom
are needed for the random orientation in a given point
towards a manipulated object. It means that a universal
mobile robot must have six and/or more degrees of free-
dom. A mechanical conception of the mobile robot is deter-
mined by a number of degrees of freedom.
Accuracy of inertial sensors plays the key role in the
autonomous navigation. Errors of the current inertial sensors
achieve the value of about 0.01/h for gyroscopes and
100 mg for accelerometers. The aforementioned errors are
integrated in time and lead to the error of positioning deter-
mination expressed by inaccuracy of measurement per hour;
for modern IMU, this error is approximately 2 km/h. The
commercial price of a high-end IMU is about €100,000.
Such high performance and expensive IMUs are implemen-
ted only into the inertial navigation systems for special
applications when the highest possible accuracy is required.
The analysis of dynamic qualities
of an electronic gyroscope
Inertial navigation is based on measuring the relative
movement of a mobile object (any object such as airplane,
automobile, robot, etc., the location, velocity and orienta-
tion in space of which need to be continuously deter-
mined), grounded on the known initial position. From
the initial value, the size, the direction of acceleration
action and the angular velocity are measured, as well as
the double integration, with respect to time and for the
purposes of obtaining accurate information about relativ-
ity motion, is performed.
The possibility of the utilization of electronic gyro-
scopes in robotic systems issues from their metrological
parameters in determining the data as well as from dynamic
characterizations. The analysis of the mentioned para-
meters was determined by measuring on a laboratory
model, which is created by a test electronic gyroscope, a
discrete linear drive and a control microcomputer.
12
The
linear discrete drive is realized by the four-phase KM,
which by means of the SD20M MICROCON control sys-
tem is operated by the MCBSTM32C (ARM) development
Turygin et al. 3

board. A gear of control impulses to linear periodic motion,
which is scanned by an inertial sensor of acceleration, was
achieved by controlling and mechanical arrangement. A flow
chart of an electric drive model is illustrated in Figure 2.
The principle of monitoring is based on the scanning of
acceleration of linear periodic motion by the MEMS sen-
sor. Next, the analysis of the influence of acceleration
dynamic changes by different modes of driving a stepper
motor follows. Prior to scanning the acceleration of the
linear periodic motion, a sequencer was set for basic micro-
stepping so that the influence of a shape of the KM actuat-
ing current was the most striking on the scanned
acceleration of a rotor. Signals were scanned to a PC by
a constant period T¼1.22 ms by means of the Analog
Device – ADIS163xx Evaluation Software – Rev 14.
A graphic environment in MATLAB with the utilization
of functions for the discrete Fourier transform and filtration
(Figure 3) was created for the analysis of the measured
signals. A bandpass filter is needed to identify an item
distinctive for the analysis of dynamic parameters of the
electronic gyroscope. The MATLAB fir1 function was used
to propose the filter. The fir1 function uses a classical win-
dow method of a proposal of the digital Finite Impulse
Response (FIR) filter with a final impulse response. A vector
of b-coefficients is returned by the function. Using the FIR
bandpass filter in the interval from 11 Hz to 33 Hz, the
courses in the time area for a used actuating signal are
obtained. In Figure 4, there is a time function with a medium
value of the acceleration amplitude 7.1 10
3
ms
2
, which
responds to the sinus actuating signal, and in Figure 5, there
is a time function with a medium value of the acceleration
amplitude 10.2 10
3
ms
2
, which responds to the special
actuating signal.
The ADIS16355 inertial sensor
The ADIS16350 sensor seems to be a suitable inertial sen-
sor. The ADIS16350 sensor is the inertial sensor for mea-
suring angular velocity and acceleration in three axes. The
sensor consists of the MEMS components and circuits of
signal processing with the aim of a highly integrated solu-
tion. Calibrated digital measurements of position and accel-
eration are thus enabled.
13,14
The sensor output data are
accommodated to the communication by the SPI bus stan-
dard. The SPI bus guarantees structurally a simple input–
output interface and the comfort of programming. The
characterizations of a described sensor with a rising
working temperature are markedly deteriorated. The
ADIS16350 electronic gyroscope achieves higher tempera-
ture resistance.
15
From the basic technical parameters of the ADIS16355,
the sensor follows that it is needed to provide its operation
in thermally stabilized space. As the sensor shows devia-
tions in measuring depending on time, as long as this data
increases exponentially, carrying out of the sensor calibrat-
ing in short time intervals is needed. The calibration lies in
a transfer of the mobile robot arm to a reference point (i.e. a
point with known coordinates from zero points of a
machine and work piece, e.g. X, Y, Z, OX, OY ¼0, 0, 0,
0, 0). After this work, it is controlled whether a monitored
measuring system shows zero coordinates. If different data
are shown, an instruction for correcting the measuring sys-
tem comes and, by means of it, the system is set up to the
reference coordinates/the reference point.
The integration of several navigation systems is a com-
plex process; however, thanks to the availability of high
quality and accurate sensors such as ADIS16350 and its
heat-calibrated equivalent ADIS16355, it currently repre-
sents a suitable and sufficiently accurate alternative to
expensive and super accurate primary navigation system.
A flow chart of the inertial system applied
in the controlling of the mobile robot
The control computer, as it is illustrated in, is a basic part of
the system. Signals from sensors are processed and evaluated
by the control computer, and on their basis, it carries out an
action hit by which the mobile robot arm motion is provided
(e.g. a process of welding after a required trajectory). The
mobile robot can work in an automatic mode but also in a
manual mode when the control computer processes and car-
ries out instructions from a service of the mobile robot. The
control computer communicates through the A/D converter
with a block controlling the process of welding, and thereby,
it also controls the process of welding.
Servomotors have circuits (interpolator, bidirectional
counter and incremental scanner of position) that are able
to regulate the velocity of motion. This is used mainly in
the manual mode when the velocity of motors is lowered
due to the protection and safety of the service. An incre-
mental scanner of position generates an impulse by the
change of position of a servomotor shaft about a unit of
position. The impulses from the interpolator and incremen-
tal scanner of position are added up in the bidirectional
counter in such a way that in a required positive motion,
the impulses from the interpolator are added up and they
Figure 2. A flow chart of an electric drive model.
4International Journal of Advanced Robotic Systems

Figure 4. The FIR signal filtered off by a bandpass filter – the sinus actuating shape.
Figure 3. A graphic environment in MATLAB for the analysis of measured signals. A course in a time area together with the DFT in a
sinus actuating shape of the KM is illustrated. DFT: discrete Fourier transform.
Turygin et al. 5

are subtracted from the incremental scanner. An error vol-
tage arises in the output. In a polarity of this voltage, a
sense of the error is expressed. An amplifier is connected
either to the bidirectional counter or to the scanner of abso-
lute position; its shaft is joined tightly with the servomotor
shaft by means of the gear. Switching is controlled by the
control computer, by which the velocity information is
given to the interpolator and a value of new position is
given to the register of position.
A camera is connected to the control computer via the
A/D converter. Signals from the camera are analysed and
utilized for the control of welding accuracy. A touch sensor
is represented by an infrared (IR) detector, which serves for
detecting obstacles in a near environment of the mobile
robot, the tens of centimetres. This sensor provides a binary
signal – it detects a reflected IR signal/it doesn’t detect a
reflected IR signal or it detects an obstacle/it doesn’t detect
an obstacle. These sensors are utilized in setting up the zero
and reference points; they are also utilized in guiding the
arm to these points in order to avoid a collision between the
arm and work piece in the raid to the reference position.
An IMU block consists of gyroscopes, accelerometers
and temperature sensors (Figure 6.). The mobile robot arm
motionisrecordedbythem,andtheinformationabout
direction and velocity of motion is given to the navigation
computer, by which the information is given to the control
computer. The information is depicted on a display by the
navigation computer, then it is compared with the coordi-
nates required by the program or service, and consequently,
the motion of the mobile robot is controlled in order to
achieve the required coordinates. Connecting between the
INS (IMU þnavigation computer) and the control
computer is realized through the SPI duplex bus. Next, the
mentioned bus is used for resetting the inertial system or
triggering diagnostics and system tests.
An application for the controlling of
the mobile robot by the inertial system
In implementing the inertial system to the controlling of an
industrial and mobile robot with five degrees of freedom,
the connecting to a control process computer is also
needed. To connect the mobile robot to the control com-
puter is the most frequent and the simplest way of control-
ling in practice.
The immediate position of single mechanisms of the
mobile robot is identified by a common control system via
integrated position sensors. By implementing the inertial
system on a mobile robot arm, the position sensors are not
needed, and the arm position is evaluated by an autono-
mous inertial system. The mobile robot arm position is
evaluated by the mentioned system on the basis of knowl-
edge in the initial (reference) position and subsequent scan-
ning of the arm motion by the inertial sensor.
The considerations and results mentioned in the previ-
ous section can be applied wherever GPS navigation is not
available and where it is necessary to accurately identify
the monitored object. The collected information can be
utilized in designing a mobile robot with a control program
able to review its position in the real coordinate system, and
thus, it is suitable for navigation even in unfamiliar envi-
ronment (e.g. in an underground geological survey).
16
An application mobile robot has five degrees of free-
dom. It means that it works in the 3D coordinate system X,
Figure 5. The FIR signal filtered off by a bandpass filter – the special shape of actuating.
6International Journal of Advanced Robotic Systems

Y and Z. The next two degrees of freedom are in the rotary
movements of the mobile robot arm (welding robot), as
illustrated in Figure 7.
After switching off, the control system loses the infor-
mation about position. Therefore, there is a reference point
on the mobile robot. The system recognizes the distance of
the reference point from zero points of the machine and
work piece.
17,18
Therefore, after switching on, the mobile
robot arm must be given to the initial point by the system,
so that the initial (reference) coordinates were set up. The
coordinates of the reference point are determined by the
position of the sensor, and they can be changed according
to the need in the pod MENU – CALIBRATION AND
TESTS OF SENSORS. After switching on the system, the
TEST INS function is activated as the first.
The course of the TEST function is as follows: the
mobile robot arm is set up to the position of the reference
point and it is controlled whether the coordinates consistent
with the coordinates of the reference point are returned by
the inertial system. If not, the inertial system for the defined
coordinates is calibrated. Then, the arm transfer to the
maximum coordinates follows. It is then controlled
whether the coordinates consistent with the coordinates
of the maximum point are returned by the inertial system.
If not, the correct coordinates are set up in the inertial
system. After these steps, the inertial system is calibrated,
and the functions of the mobile robot can be opened up.
The TEST function, which is carried out after activating
the mobile robot, is necessary for the correct function of the
inertial system applied in the controlling of the mobile
robot. Consequently, the motion to the reference position
of the mobile robot arm after each manufactured product is
performed. This mode is also utilized in classical gauging
systems, which are equipped with relative sensors of the
IRC position (e.g. CNC machines). The calibration of the
system is realized by guiding the movable part to the ref-
erence position after each machined piece work.
Conclusion
The development in the sphere of MEMS technology
brings new, complex (also affordable) solutions of sensors
suitable for integrated navigation systems with extensive
possibilities of utilization.
6
The submitted contribution represents the original way
of controlling the mobile robot by the inertial system. Sen-
sors of position, selsyns, are used in classical mobile robots
for determining the actual position of their parts (gripper
Figure 6. A flow chart of the robot with the applied inertial system.
Figure 7. A schematic representation of the mobile robot with
the applied inertial system.
Turygin et al. 7

and arm). The inertial system is responsible for determining
the actual position in the described system of controlling the
robot. Regular calibration of sensors deflection is a neces-
sary for the correct activity of the inertial system. If the
condition was not fulfilled, the deflection would constantly
grow, and big differences between the real position of the
robot and the position given by the inertial system would
appear. In practice, it is inadmissible. Inertial systems are
constantly developed; therefore, by improving the sensors,
mainly by minimizing the errors of accelerometers and gyro-
scopes, more perfect and accurate inertial systems appear.
19
The proposed mobile robot is able to work autono-
mously, automatically according to the program or manu-
ally according to the instructions from the service. The
instructions of the service are given by means of a key-
board. The improvement of manual controlling the mobile
robot would be the use of an arm-eye system, which would
markedly improve the possibilities of the service to use the
mobile robot more effectively.
The possibilities of utilizing the inertial systems are
directly proportional to the advance in their development.
The ability of precise measuring the position of the mobile
robot mainly in necessarily regularly repetitive calibration
is increased by this. The implemented INS is able to mea-
sure accelerating and slewing of robotic arm watched point
and thus to determine the position of the mobile robotic arm
in space.
19
The configured first hardware and software is able to
achieve the needed values of measuring the position and
even on the 3D surface.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support
for the research, authorship, and/or publication of this article: This
publication is the result of implementation of the project
‘UNIVERSITY SCIENTIFIC PARK: CAMPUS MTF STU –
CAMBO’’ (ITMS: 26220220179) supported by the Research and
Development Operational Program funded by the EFRR.
References
1. Beeby S, Tudor J and White NM. Energy harvesting vibration
sources for micro systems applications. Meas Sci Technol
2006; 17: 175–195.
2. Sotak M, Sopata R, Breda J, et al. Integration of navigation
systems. (Monograph, Kosˇice), 2006.
3. Brenner M. Integrated GPS/inertial fault detection availabil-
ity. Navigation 1996; 43(2): 111–130.
4. Farell JA and Barth M. The global positioning system and
inertial navigation. 1st ed. Mishawaka: McGraw-Hill Profes-
siona, 1999, p. 340.
5. Analog Devices, Inc. Mixed-signal and digital signal process-
ing ICs|Analog Devices Internet. Updated: 2009. http://www.
analog.com/media/en/technical-documentation/data-sheets/
ADIS16350_16355.pdf (2007, accessed 4 May 2016).
6. Grewal MS, Weill LR and Andrews AP. Global positioning
systems, inertial navigation, and integration. 2nd ed. New
Jersey: Wiley, 2007, p. 416.
7. Lin W, Lee S, Li SS, et al. 60-MHz wine glass micromecha-
nical disk reference oscillator. In: Solid-State Circuits Con-
ference, Digest of Technical Papers, ISSCC, 15–19 February
2004. San Francisco, CA: IEEE.
8. Kopa´cˇik A. Inertial measurement systems. Bratislava: SAV,
1998.
9. Beeby SP, Torah RN, Tudor MJ, et al. Micro electromagnetic
generator for vibration energy harvesting. J Micromech
Microeng 2007; 17(7): 1257–1265.
10. Coffee JR and Maganty P. An integrated DGPS/INS naviga-
tion system for a balltistic missile: design and flight test
results. Navigation 2001; 43(3): 273–794.
11. Kayton M. Navigation: ships to space. IEEE Trans Aerosp
Electron Syst 1988; 24(5): 474–519.
12. Napier M. Integration of satellite and inertial positioning sys-
tems. J Nav 1990; 43(1): 48–57.
13. Krasovsij AA, Beloglazov IN and C
ˇigin GP. Teorija korrel-
jacionno- ekstremal´
nych navigacionnych sistem. Moskva:
Nauka, 1979.
14. Vesely
´V and Nguyen QT. Robust decentralized controller
design for large scale systems: subsystems approach. Acta
Montanistica Slovaca 2011; 16(1): 84–88.
15. Schmidt GT and Phillips RE. INS/GPS integration architec-
tures, RTO NATO EN-SET-064.Advances in navigation sen-
sors and integration Technology. Paper presented at Research
and Technology Organisation North Atlantic Treaty Organi-
sation, 20–21 October 2003, London, 2004.
16. Blisˇt
ˇan P. Presentation of geological date in geographic infor-
mation systems. Acta Montanistica Slovaca 2007; 12(3):
329–334.
17. Roundy S. Energy scavenging for wireless sensor nodes
with a focus on vibration to electricity conversion.Disserta-
tion. University of California at Berkeley, Berkeley, CA,
2003.
18. Bar-Shalom Y, Li XR and Kirubarajan T. Estimation with
applications to tracking and navigation: theory algorithms
and software. John Wiley & Sons, Inc. New York, 2001.
19. Boz
ˇek P and S
ˇuriansky J. Controlling robot on the inertial
basis. Proceedings of scientific articles. Transactions of the
VS
ˇB – Technical University of Ostrava, Mechanical Series
No. 1, vol. LVII, 2011, pp. 9–18.
8International Journal of Advanced Robotic Systems