The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control
The generalized frame of autonomous robot control system is represented and the data preparation for the
 simultaneous localization and mapping (SLAM) by using new type of 3D sensor is described. Also the
 developed data structure for data communication between robot units, and the p...
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| Дата: | 2008 |
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| Автори: | , , , , , |
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Інститут проблем штучного інтелекту МОН України та НАН України
2008
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Цитувати: | The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control / Hubert Roth, Anatoly Sachenko, Vasyl Koval, Joochim Chanin,Oleh Adamiv, Viktor Kapura // Штучний інтелект. — 2008. — № 4. — С. 512-521. — Бібліогр.: 19 назв. — англ. |
Репозитарії
Digital Library of Periodicals of National Academy of Sciences of Ukraine| _version_ | 1860239506124308480 |
|---|---|
| author | Roth, H. Sachenko, A. Koval, V. Chanin, J. Adamiv, O. Kapura, V. |
| author_facet | Roth, H. Sachenko, A. Koval, V. Chanin, J. Adamiv, O. Kapura, V. |
| citation_txt | The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control / Hubert Roth, Anatoly Sachenko, Vasyl Koval, Joochim Chanin,Oleh Adamiv, Viktor Kapura // Штучний інтелект. — 2008. — № 4. — С. 512-521. — Бібліогр.: 19 назв. — англ. |
| collection | DSpace DC |
| description | The generalized frame of autonomous robot control system is represented and the data preparation for the
simultaneous localization and mapping (SLAM) by using new type of 3D sensor is described. Also the
developed data structure for data communication between robot units, and the protocol for client-server
interaction, and an algorithm for the data communication of client-server protocol packages allowing to
control by mobile robot in unstructured environment, and their application on real-scaled mobile robot are
presented in this paper.
Представлена обобщенная структура автономной системы управления роботом и описана подготовка
данных для одновременной локализации и отображения (SLAM) с использованием нового вида 3D
датчика. В статье также описаны разработанная структура данных для связи между автоматическими
модулями, протокол для серверного и клиентского взаимодействия и алгоритм обмена пакетами данных на
основе технологии клиент-сервер для управления мобильным роботом в неструктурированной среде, а
также их использование на работающем мобильном роботе.
Представлено узагальнену структуру автономної системи управління роботом та описано підготовку
даних для одночасної локалізації і відображення (SLAM) з використанням нового виду 3D датчика.
В статті також описані розроблена структура даних для зв’язку між автоматичними модулями,
протокол для серверної та клієнтської взаємодії та алгоритм обміну пакетами даних на основі
технології клієнт-сервер для управління мобільним роботом в неструктурованому середовищі, а
також їх застосування на працюючому мобільному роботі.
|
| first_indexed | 2025-12-07T18:28:27Z |
| format | Article |
| fulltext |
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УДК 681.3.5
Hubert Roth1, Anatoly Sachenko2, Vasyl Koval 2, Joochim Chanin1,Oleh Adamiv 2,
Viktor Kapura2
1University of Siegen, Siegen, Germany
2Research Institute of Intelligent Computer Systems, Ternopil National Economic University,
Ternopil, Ukraine
hubert.roth@uni-siegen.de, as@tneu.edu.ua
The 3D Mapping Preparation using 2D/3D
Cameras for Mobile Robot Control*
The generalized frame of autonomous robot control system is represented and the data preparation for the
simultaneous localization and mapping (SLAM) by using new type of 3D sensor is described. Also the
developed data structure for data communication between robot units, and the protocol for client-server
interaction, and an algorithm for the data communication of client-server protocol packages allowing to
control by mobile robot in unstructured environment, and their application on real-scaled mobile robot are
presented in this paper.
Introduction
Mobile robots (MR) as universal technical systems that can provide mechanical activity
are one of the modern trends of scientific research in the field of robotics. Widespread
applications of intelligent mobile robots are different fields of human activity is a confirmation of
the timeliness of the researches. These applications are oriented towards in-door environments
constructed by humans and for external unstructured environments, where these systems are used
in ground, aerial, space or under-water oriented applications. There is an especially important
application of mobile robots in aggressive unstructured environments that are dangerous or
impossible for human activity such as man-caused catastrophes, fire or terrorist acts.
Nowadays there are a lot of known architectural decisions for MR navigation on the
executive, tactical and strategic level in static environments [1-4]. If the environment is unstruc-
tured one may either provide sophisticated planning, decision making and control schemes or
one may force structure onto the environment. Therefore the analysis of such decisions will
allow to design optimum configuration of interrelations of the main MR modules for providing
obstacle avoidance navigation in dynamic unstructured environments. A lot of mobile robot
structures are mostly related to static priory known environments or at list are standalone that
need to be combined in order to reach the joint benefit for MR navigation in unstructured
environment. For this purpose it is proposed the generalized structure of the autonomous mobile
robot control system presented on Fig. 1. that is a basis for providing of the MR navigation in un-
structured environment and shows the general subtasks interconnection and for MR
navigation.
Taking into account the productivity of computing means that are necessary for func-
tioning of MR, the MR subsystems can be realized using monoprocessor systems or the specia-
lized tools, for example, using multiprocessor subsystem. The monoprocessor systems based on
the personal computers (PC) compared with the specialized tools have the less computing speed
* The authors are grateful for the support of the Ministry of Education and Science of Ukraine and
International Bureau of the Federal Ministry of Education and Research of Germany, German Aerospace Center
within the International research project 0108U004785 “Development of stereovision methods and devices for
autonomous navigation of mobile robots”.
The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control
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however are more simple in realization, have the wide instrumental resources kit for programs
development using different programming languages. Taking into account the high growth of PC
productivity and capacity of main memory and at the same time decreasing their cost, the ques-
tion of processing speed becomes not too critical. The other advantage of PC is the openness of
the system. That possibility allows constructing any configuration including use of one system
board and small set of peripheral units. Besides, operating systems developed for PC allow to
realize the real-time mode, for example UNIX, LINUX, WINDOWS. However, taking into
account the large number of tasks for MR control (Fig. 1) and significant processor time for it’s
execution it is necessary to input the supervisor program which would operate within the
operating system.
Figure 1 – The generalized structure of an autonomous mobile robot control system
According to the generalized structure, depicted on Fig. 1, the data flow from Mobile
Robot Hardware provided by vision system of MR. In this paper the new type of 3D sensors for
the MR vision sysmen are presetned. Recently, the development of Photonic Mixer Devices,
PMD camera, which enables 3D image grabbing within a few milliseconds give an important
impulse in visual sensing for 3D perception. PMD-based device has still limited resolution and
provide only gray scale information. Therefore, the combination of 2D/3D vision system is
proposed to inundate this limitation, and to provide more realistic 3D color images in order to
prepare the future data for the simultaneous localization and mapping (SLAM).
1. The principle of PMD camera
The Photonic Mixer Devices entitled PMD sensors as a smart pixel can be an integration
element for a 3D imaging camera chip based on standard CCD- or CMOS-technology (Fig. 3.).
The main feature is an array sensor, which can measure the distance to a target in parallel without
scanning. The key execution is based on Time-Of-Flight (TOF) principle (Fig. 2). A light pulse is
transmitted form a transmitter unit and the target distance is measured by determining the turn
around time from a transmitter to a receiver. According to the speed of light theory, the interval
distance can be easily calculated.
Figure 2 – TOF principle
The Unit for
Local Map
Building of
Mobile Robot
Localization
Unit of Mobile
Robot
Path Planning
Unit of Mobile
Robot
Vision System
readings
Control Signals
to Actuators
Goal of the
Movement
The Unit for
Global Map
Building of
Mobile Robot
Vision System
Processing Unit
Mobile Robot
Hardware
Knowledge
Base
1
2
3 4
5 7
8
6
Roth H., Sachenko A., Koval V., Chanin J., Adamiv O., Kapura V.
«Искусственный интеллект» 4’2008 514
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The PMD chip is a prominent component, its pixel provides the depth information of
corresponding point in the object plane. The PMD has the advantages of fast imaging and
excellent depth information for scene capture. This camera can also enable fast optical sensing
and demodulation of incoherent light signals in one component. It additionally provides both the
intensity as well as the distance in each pixel. Currently, the PMD sensor devices provide the
resolutions of 48x64, 64x16 and 160x120 pixels. A common modulation frequency is 20 MHz,
which results in an unequivocal distance range of 7,5 to 40 meters. The principle of how a
simplified PMD sensor calculates the distance between obstacle and camera is to analyze a phase
shift. The depth data results from the phase shift of the out-coming and the incoming signals. The
equation for the autocorrelation is:
T
dttxtxc
0
)()()( , (1)
where T is time of integration, the correlation is done using four samples 41...CC with time
interval of 4T and phase shift )( .
)arctan(
42
31
CC
CC
. (2)
The distance )(d can be easily calculated to:
mod
0
.4
.
f
cd
, (3)
where 0c is the speed of light and modf is the modulation frequency, a common value of the
modulation frequency is 20MHz.
a) b) c)
Figure 3 – PMD camera a) A2; b) 19k; c) PMD sensor
The light source capability and the noise suppression
Ideally, powerful light source is desired for long distance detection. In reality the
construction of the light source is mainly limited by the maximum switching frequency and the
power dissipation. For detection range of 40 meter, a high power light module is required. From
construction point of view the laser and LEDs light source are both capable according to their
high switching frequency and low power consumption.
2. Image registration
The 3D mapping is acquired by a movement of mobile robot name “TOM3D” (Tele
Operated Machine with 3D PMD-camera) (Fig. 4). It can be used for high performance indoor
and outdoor off-road. When the robot is moving through the scene, the 3D geometry is collected
by 2 sources camera at the same time. The depth data is obtained from PMD while texture is
mapped from 2D camera. The resolution of the 3D data from PMD camera (64*48) is 10 times
less than 2D camera (640*480). By using both of these two cameras, high resolution, gray scale
The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control
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image and depth data can be attained. The gray scale image from PMD camera is only used for
the first time to calibrate camera, after that this data is ignored. The interpolation method then
uses for adjusting PMD image size in order to be equal with 2D data set. Fig. 5 illustrates
interpolation depth and 2D data. Each depth data register to the nearby 2D 10 pixels. The bunch
of pixels has the same depth data as in equation (4).
),(),( 1010
2
m
m
n
nDmnpmd jiQyxP
.
(4)
sizeQnm max,
pmdP is the new matrix depth data and DQ2 is the RGB data from 2D camera. Then, the 3D
mapping yields the texture for the 3D model. OpenGL subsequently uses to display the entire 3D
mapping output. The proposed method straightforwardly presents the achievement of 3D
mapping building. This ensures an easy calibration of both cameras and there is only small loss
of information. The overall process for generate 3D mapping shown in Fig. 6. It is separated into
4 blocks, which are PMD depth data capture, RGB data capture, image registration and mobile
robotic localization. In this paper, the algorithm initializes to register 2D/3D image in the third
block. The mobile robot TOM3D is used in a test platform. It is equipped with PMD camera, 2D
camera, 16 bit microcontroller and embedded PC.
Figure 4 – Mobile robot TOM3D 2/3D cameras
Figure 5 – Registration and rescale image sets
Roth H., Sachenko A., Koval V., Chanin J., Adamiv O., Kapura V.
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Figure 6 – Diagram of 3D mapping
3. The Proposed Structure of Software
In this paper it is proposed the software structure of mobile robot according to the Fig. 7.
Figure 7 – The generalized software structure of an autonomous mobile robot control system
The structure of the proposed software system (Fig. 7) contains the Supervisor block
which is the kernel of software. It works invisibly for user and performs the following systems
functions: organization of MR components interrelations, monitoring of processes, distributing of
processor time between tasks and others.
The Unit of Interruption provides the events identification and processing of these events
by other blocks. Thus it provides a general synchronization of MR procedures implementation.
The blocks for connection with activators and sensors provide the data input/output using
standard interfaces, for example RS232, USB. In addition, for providing the relation with the
external MR environment, these blocks can perform the preliminary sensors data processing for
increasing accuracy and noise immunity of sensory information and also filtration of different
sort of noises. Thus the input/output of control and informative commands performs according to
the interruption called by Supervisor. This process uses the buffering and records commands in
the main memory and Data Base (DB). Such approach allows to reduce the processor usage and
to provide the analysis of received information. The information about the MR commands, local
and global maps of the environment and information about MR position are stored in DB. DB
can be used for creating of the knowledge base, which is needed for intelligent MR control. For
RAM Data Base
Unit of
Process
Visualizatio
n
Unit of Map
Building
Algorithm1
Unit
of
Interruption
Supervisor
Unit of the
relation with
actuators
Unit of the
relations with
sensors
Unit of Map
Building
AlgorithmN
The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control
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example, it is important for MR control to analyze the stored in DB data for providing the
possibility to return to previous position in the case of deadlock condition and choice other
trajectory of movement.
Unit of Process Visualization provides monitoring of MR functional activity on the screen
of display. Such mode is necessary during debugging of main procedures of MR functioning. In
the real conditions the block of monitoring should be turned off for increasing the general
productivity of computing means.
The blocks of algorithms implementation provide the realization of processes for construc-
tion of local and global maps of environment, construction of MR motion trajectory, localization,
selecting of maneuvers for movement and analysis and processing of input data. For performance
of such algorithms processor time is provided. Performance of each algorithm is completed by
the program interruption call and request to Supervisor with the message about the end of pro-
cedure of algorithm performance. On the basis of interruption Supervisor determines the sequen-
ce of performance of procedures for MR functioning, which initialized by the new interrupt.
4. Database Structure
It is important to identify the data structure and to analyze the input data flow from robot
sensors for programming of the methods of the map building of environment based on PMD
camera [5-8], for map building of mobile robot. For development of data structure it is expected
to use a relational data model (Fig. 8), that has advantages: convenience of presentation of data
structures as two-dimensional table; flexibility of the data processing in a table form; exactness
(groups relations between tables have exact maintenance and submit to the mathematical
methods of treatment with the use of algebra of relations); secrecy; clarity (relational presentation
of data gives the clear picture of relationships attributes from the different relations and files);
independence and expansibility of data (it is easily to add and delete the new corteges and
relations in the relational database); there is a facility for easily of data management; clarity and
evidentness of data presentation; possibility to design of hierarchical and nets data models for
data structures [9], [10]. In addition, the relational data structures have strongly developed level
of abstractions of mathematical tool (relational algebra, numeral methods of group’s relations
treatment, predicative logic and others).
Figure 8 – Relational data structure
5. Protocol for Client-Server Interaction
The communication between Supervisor and Sensory subsystem and Subsystem of
activators of MR is carried out on a client-server principle. Such organization of communications
is predefined by the necessity of distributing of calculable powers between the tasks of data
acquisition which can be realized on the specialized facilities, and tasks of top level, which will
be realized on PC. Co-operation between server and client parts could be provided by the
specialized protocol of data exchange that has a certain structure (Table 1), that is modification of
protocol presented in [11].
Roth H., Sachenko A., Koval V., Chanin J., Adamiv O., Kapura V.
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Taking into account the real time, in which MR works, it is expected to provide
functioning of protocols in the "silent" mode. In this mode the MR Sensory subsystem does not
give confirmation of client’s instructions execution. Such approach provides minimum time for
treatment of packets of client-server co-operation.
At the messages passing from a server to the client, the packets are transmitted periodically
with state information about MR activators and with sensors data. In a case of using protocol for
the transmission of RGB data from PMD camera with resolution 160х120 pixels, it is necessary
such quantity of data, which must be transmit by one packet through an interface and equal a
57600 byte. At that every pixel is presented by 3 bytes of colors without application of
procedures of compression. For this purpose it is enough to select 2 bytes of data (is equal to the
maximum up to 65536 bytes which can be transmitted by one packet) for the component
«quantity of transmitting bytes» of structures of packet of protocol.
If more information in client-server protocol of co-operation is needed, it is necessary to
extend a greater quantity byte for component «quantity of transmitting bytes» in the structure of
protocol packet.
In the case of transmitting messages from the client to server the commands structure in a
packet is defined (Table 2). In order to control the functioning of the client-server protocol the
client must periodically send selfsupervisory packet with the command «PULSE» to the server in
the case of absence of MR control commands. If the control commands of client or commands
«PULSE» are absent, a robot automatically stops all engines that can renew the work only after
receiving a package from client. Thus, the algorithm of client-server co-operation can be
represented by the generalized flow diagram (Fig. 9).
Table 1 – The Structure of Protocol Packet for MR Client-Server Interaction
Component Bytes Value Description
Caption 2 0хFA, 0xFB Caption of the packet is identically as for
server as for client
Quantity of
transmitting bytes
1 N+2 Quantity of transmitting bytes, including
check sum
Data N Commands Client’s commands or server’s information
Check sum 2 Calculated Check sum of packet
Table 2 – The Structure of Commands Transmitting from Client to Server
Component Bytes Value Description
Caption 2 0хFA, 0xFB Caption of the packet is identically as for
server as for client
Quantity of
transmitting bytes
1 N+2 Quantity of transmitting bytes, including
check sum
Number of client’s
command
1 0-255 Number of client’s command to server
Type of argument
(depend from type of
command)
1
0x3B
0x1B
0x2B
Type of command’s argument:
– positive integer;
– negative integer;
– string.
Argument N Data Argument of command
Check sum 2 Calculated Check sum of packet calculated during
transmitting of the packet
6. Application of the Proposed Approach
Experimental researches were carried out using the mobile robot TOM3D with a test plat-
form that is equipped with PMD camera, 2D camera and embedded PC and also using a platform
of mobile robot Pioneer P2-DX of the ActivMedia Company [11], that two driving-wheels placed
on one axle and one selforienting wheel placed on the back-end of robot and is a balance of it.
The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control
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Figure 9 – Generalized algorithm of client-server protocol work
Figure 10 – Source listing of Matlab subprogram
Roth H., Sachenko A., Koval V., Chanin J., Adamiv O., Kapura V.
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For programming and researches of the offered structures with the purpose to control by a
mobile robot the programming software Matlab® v.6.5 Release 13 were used, created by the firm
of The Math Works Inc., which is a world standard in the region of scientific and technical
calculations [12-14]. The choice of package of Matlab is predefined by its advantages [15-17]. The
created software of the Matlab provides reading, recording and calculating of checks sums for the
transmission of commands packages in mentioned protocol depicted on Fig. 10.
Conclusion
The 3D Mapping Preparation using new type of 3D sensor for Mobile Robot Control is
presented in this paper.
Another results of the researches that is presented in this paper is the developed structure of
top level software for mobile robot control using the analysis of informative threads between the
programming units that allows to present data on datalogical levels for building of the mobile
robot map of the environment and also adapting of the client-server protocol, which provides
data interaction for MR control. Taking into account the universality of the operating systems
like Windows, UNIX, LINUX that use processor time for own necessities, it is reasonable to
implement the top levels software using high-level languages, while communication subsystems
with the peripheral devices and sensors – on microprocessors.
Fig. 11 (a) and (b) show the raw data from 2D/3D cameras before enhancement.
Fig. 11 (c) demonstrates the registered image. It can be seen that the 3D image has more
texture information, which is better than using the information only from 2D or 3D camera.
However, the texture of registered image seems lacking from the raw data due to the
differentials of rescale and quality of 2D/3D cameras. The quality of output will be
improved by the better quality of 2D camera and increasing pixel of PMD camera in the
upcoming future. The schemes of the 3D preparation image will be used in order to
generate the future simultaneous localization and mapping.
a) b) c)
Figure 11 – Registration image
a) Image from 2D camera; b) Depth data from PMD Camera; c) Registered image.
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Hubert Roth, Анатолий Саченко, Василий Коваль, Joochim Chanin, Олег Адамив, Виктор Капура
Подготовка 3D отображения с использованием 2D/3D камер для управления мобильным роботом
Представлена обобщенная структура автономной системы управления роботом и описана подготовка
данных для одновременной локализации и отображения (SLAM) с использованием нового вида 3D
датчика. В статье также описаны разработанная структура данных для связи между автоматическими
модулями, протокол для серверного и клиентского взаимодействия и алгоритм обмена пакетами данных на
основе технологии клиент-сервер для управления мобильным роботом в неструктурированной среде, а
также их использование на работающем мобильном роботе.
Hubert Roth, Анатолій Саченко, Василь Коваль, Joochim Chanin, Олег Адамів, Віктор Капура
Підготовка 3D відображення з використанням 2D/3D камер для управління мобільним роботом
Представлено узагальнену структуру автономної системи управління роботом та описано підготовку
даних для одночасної локалізації і відображення (SLAM) з використанням нового виду 3D датчика.
В статті також описані розроблена структура даних для зв’язку між автоматичними модулями,
протокол для серверної та клієнтської взаємодії та алгоритм обміну пакетами даних на основі
технології клієнт-сервер для управління мобільним роботом в неструктурованому середовищі, а
також їх застосування на працюючому мобільному роботі.
Статья поступила в редакцию 29.07.2008.
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| id | nasplib_isofts_kiev_ua-123456789-7555 |
| institution | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| issn | 1561-5359 |
| language | English |
| last_indexed | 2025-12-07T18:28:27Z |
| publishDate | 2008 |
| publisher | Інститут проблем штучного інтелекту МОН України та НАН України |
| record_format | dspace |
| spelling | Roth, H. Sachenko, A. Koval, V. Chanin, J. Adamiv, O. Kapura, V. 2010-04-02T11:00:19Z 2010-04-02T11:00:19Z 2008 The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control / Hubert Roth, Anatoly Sachenko, Vasyl Koval, Joochim Chanin,Oleh Adamiv, Viktor Kapura // Штучний інтелект. — 2008. — № 4. — С. 512-521. — Бібліогр.: 19 назв. — англ. 1561-5359 https://nasplib.isofts.kiev.ua/handle/123456789/7555 681.3.5 The generalized frame of autonomous robot control system is represented and the data preparation for the
 simultaneous localization and mapping (SLAM) by using new type of 3D sensor is described. Also the
 developed data structure for data communication between robot units, and the protocol for client-server
 interaction, and an algorithm for the data communication of client-server protocol packages allowing to
 control by mobile robot in unstructured environment, and their application on real-scaled mobile robot are
 presented in this paper. Представлена обобщенная структура автономной системы управления роботом и описана подготовка
 данных для одновременной локализации и отображения (SLAM) с использованием нового вида 3D
 датчика. В статье также описаны разработанная структура данных для связи между автоматическими
 модулями, протокол для серверного и клиентского взаимодействия и алгоритм обмена пакетами данных на
 основе технологии клиент-сервер для управления мобильным роботом в неструктурированной среде, а
 также их использование на работающем мобильном роботе. Представлено узагальнену структуру автономної системи управління роботом та описано підготовку
 даних для одночасної локалізації і відображення (SLAM) з використанням нового виду 3D датчика.
 В статті також описані розроблена структура даних для зв’язку між автоматичними модулями,
 протокол для серверної та клієнтської взаємодії та алгоритм обміну пакетами даних на основі
 технології клієнт-сервер для управління мобільним роботом в неструктурованому середовищі, а
 також їх застосування на працюючому мобільному роботі. The authors are grateful for the support of the Ministry of Education and Science of Ukraine and International Bureau of the Federal Ministry of Education and Research of Germany, German Aerospace Center within the International research project 0108U004785 "Development of stereovision methods and devices for autonomous navigation of mobile robots". en Інститут проблем штучного інтелекту МОН України та НАН України Управление и информационное обеспечение мехатронных и робототехнических систем The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control Подготовка 3D отображения с использованием 2D/3D камер для управления мобильным роботом Підготовка 3D відображення з використанням 2D/3D камер для управління мобільним роботом Article published earlier |
| spellingShingle | The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control Roth, H. Sachenko, A. Koval, V. Chanin, J. Adamiv, O. Kapura, V. Управление и информационное обеспечение мехатронных и робототехнических систем |
| title | The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control |
| title_alt | Подготовка 3D отображения с использованием 2D/3D камер для управления мобильным роботом Підготовка 3D відображення з використанням 2D/3D камер для управління мобільним роботом |
| title_full | The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control |
| title_fullStr | The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control |
| title_full_unstemmed | The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control |
| title_short | The 3D Mapping Preparation using 2D/3D Cameras for Mobile Robot Control |
| title_sort | 3d mapping preparation using 2d/3d cameras for mobile robot control |
| topic | Управление и информационное обеспечение мехатронных и робототехнических систем |
| topic_facet | Управление и информационное обеспечение мехатронных и робототехнических систем |
| url | https://nasplib.isofts.kiev.ua/handle/123456789/7555 |
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