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                RobomapStudio is a smart tool designed to process data in the field of autonomous robotics and artificial intelligence. The aim of this project is off-line work with data from 2D LS scanner SICK – PLS100. All algorithms included into this project fall into a relatively young scientific area - evolutionary robotics. The program consists of more than 50 parts suitable to solve the problems such as continual robot localization, global robot localization and SLAM + necessary subsidiary tools. A small indoor office or small cluster of offices is the most suitable working environment. The program includes powerful 2D LS simulator able to simulate data of the 2D LS. Evolutionary algorithms are substantial part of the RobomapStudio. Powerful n-dimensional simulator is able to test more than 65 standard benchmark functions using several EA optimizers – SGA, aGA, MonteCarlo, DE, JADE, JDE, PSO, RPSO, pureCMA-ES. RobomapStudio cooperates with well-known matrix laboratory MATLAB and uses this program like subsidiary tool at visualization.

 

RobomapStudio is 32/64 bit application. RobomapStudio was designed to operate under 32 bit and 64 bit version of Windows 2000 SP4, XP SP2/SP3, Vista, 7 and 8. RobomapStudio was fully tested under VMWare 6,7,8,9,10.xx, MS Virtual PC 2007 and VirtualBox.

 

 

www.openslam.org

 

 

 

 

 

 

 

 

  DESCRIPTION 

 

RobomapStudio(RS) is a smart tool permitting to process various data types in the field of autonomous robotics. (RS) works with vector data only. The main goal of this project is to provide an analytical tool capable of estimating possibilities of the robot navigation using 2DLS. The data from 2DLS can be obtained from real 2DLS Sick – Sick GmbH for example or from computer simulator. (RS) contains three powerful simulators. All computations proceed with geometric primitives – lines.

 

CONTINUAL LOCALIZATION AND GLOBAL LOCALIZATION IN A KNOWN ENVIRONMENT WITH OR WITHOUT MOVING OBJECTS

CASCADED ESTIMATORS – MOVING OBJECTS DETECTION

inputoutput .jpg

 

 

 

MAP BUILDING – gSLAM ALGORITHM, A SMALL ENVIRONMENT WITHOUT MOVING OBJECTS

 

 

 

The number of the geometric primitives is limited to approx. 100 lines if 1xCPU-AMD2.2GHz/Orleans is used. If number of the model lines is less than 60, computations can be real-time. The higher computing power provides possibility to use more lines. There are no constraining limits in the sense of the minimum grid resolution. (RS) uses universal measuring units - 1x1unit. Usually this unit is equal to 1cm (1x1cm or 2.5x2.5cm etc.) according to the 2D LS scale. The maximum size of environment is 32000x32000cm(units) for the internal map builder and 64000x64000cm(units) if the external map builder is used (AutoCAD+CSV for example). The maximum angle resolution is usually 0.5°, some parts of the (RS) use IEEE(double) resolution in heading. The number of rays of 2DLS can be changed. The recommended number of rays is 361 in 180°.

 

(RS) uses its own data-file formats. The map import or any suitable data format from 2DLS is possible using built-in tools. The acceptable map formats are TXT(CSV) or simplified PLT file format style. A bitmap picture can be traced. It is possible to import the data from AutoCAD due to the DXF, DWG, HPGL, DNG file type converter. All maps in this formats have to be inserted to internal tool and exported to HPGL-1(PLT) file type. (RS) does not use general HPGL-1 file format – simplified PLT format is used.

 

The most important results provided by (RS) can be stored in a special data-file type (PTH) and it can be used as a ‘playback’ later for better review. Thanks to several powerful 2DLS simulators, data from 2DLS can be simulated from the geometric map of environment and exported to TXT(CSV) file type. The first mentioned simulator uses a classic vector map representation. The second one uses a bitmap representation. This simulator has no restriction in the sense of the maximum recommended 2D dimensions.

 

Manhattan peninsula Poster + B&W bitmap + Vectorized map in (RS) simulator 8000x8000cm

manhattanmap.jpg

manhattanmap.bmp

manh map.bmp

 

The number of beams of the used 2DLS is set to 361 by default, but this setting can be changed into a different suitable value (90,180,270 etc.). The maximum detectable obstacle is set to 6000cm. This value can be changed, but 6000cm is a recommended value for all experiments. (RS) uses MATLAB tool at visualization. Version 5.4 was used at development time, but this version can be replaced by any of the new version of this software. All necessary configuration information can be found in the configuration file.

 

1.jpg    2.jpg

 

(RS) is capable to provide localization scheme using ‘point-to-point’ and ‘point-to-line’ methodology. Evolutionary algorithms such as SGA, MonteCarlo, DE, PSO, RPSO, CMAES can be used as a computation accelerator. Identical tools are provided for global localization.  The significant part of the (RS) is cascaded pose estimators. Brute force and the classic gradient (hill climbing) method can be used. Evolutionary computation methods are a very powerful tool. The cascaded estimators use these algorithms as an accelerator too. (RS) contains all necessary viewers for all internal file types and beside this, CSV file type is supported too.

(RS) is equipped by suitable tools for bulk data processing. It contains easy multi-process management service capable of launching and controlling many (RS) instances. Thanks to the auto-priority scheduler all instances can run at once. Output data provided by (RS) can be directly processed in MS Excel or similar programs. All resulting data are in TXT format with fix syntax. MSSQL language can be used in MS Excel to data post-process. Auto-save at the end of bulk-data-process and auto-exit function with the sound signal is provided too. Almost all parts of the (RS) provide a possibility to save actual working parameters setting and use these data later. 

 

3.jpg

 

(RS) contains several modules for Simultaneous Localization and Mapping (SLAM). The basic module is so called ‘GeometricSLAM’. This module uses geometric primitives only. It is suitable for small indoor office environment. SLAM only uses one information source: 2DLS. gSLAM is very sensitive to correct setting of the working parameters. Unfortunately, identical setting for different types of environments was not found. Open areas with several static objects – it is more suitable environment. The base condition for successful map building is that all beams reflect walls. In large environment, some beams can’t be used because max. LS range is usually 5-8meters. Longer beams can be marked automatically in SLAM module (before start) according to the predefined beam-length. Such beams will not to be used for SLAM process. ‘GeometricSLAM’ is very sensitive to the lack of beams in scan. Large absence of beams can lead to SLAM malfunction. For algorithmic simplification, the map of environment is necessary too. Such map defines min/max coordinates only. Map can be replaced by ‘reticle’ with appropriate dimensions. ‘Reticle’  defines min/max coordinates too . Oblong ‘reticle’ is strongly recommended. ‘Reticle’ encloses the map and defines the min/max coordinates. Possible formats:

 

reticle SLAM.jpg

 

SLAM can use classic brute force/gradient mechanism or EA computation (simple EA or cascaded EA estimator). The nenu is divided into several ‘tabPages’. Simple EA estimator (tabPage ‘Scanner’ is activated only) is able to build most of all small office environments. Cascaded EA estimator can be used too. This ‘power-machine’ is very sensitive to the correct setting, but provides good results in suitable types of environments. (RS) SLAM builder is suitable to the environment without moving objects. gSLAM algorithm presented in (RS) does not use closing-loop technique at this time and data from 2DLS are used only – no KalmanFilter and odometry information are incorporated into gSLAM.

 

Evolutionary computations are a significant part of the (RS). More than 50 standard benchmark functions can be tested in many different configurations. More than 300Dim functions can be tested (nonscalable multidimensional testing). Used algorithm is able to repeat all tests and compute average values from for example 10000 repeating of the selected EA function(s). EA module has built-in auto-priority scheduler. Thanks to this feature many different functions can be tested at once. All functions can be visualized in its 3Dim version thanks to the Matlab visualization tool. MonteCarlo is a sub-part of SGA, aGA and DE optimizers. All modules provide video creation functions. Two dimensional EA- module cooperate with the global localization module and use GAB file format to simulate behavior of the SGA, aGA, PSO, RPSO optimizers at a global robot localization problem.

 

EA.jpg

 

To avoid using the classic and complicated job-scheduler, (RS) has a simplified priority-master/slave scheduler system. If results in the bulk-data processing style are required, this scheduler provides a great helper. Once ‘master’ module is running and paused by ‘stop/pause’ button, many other modules can be run in ‘iddle’ mode simultaneously. ‘Master’ or ‘Iddle’ mode is set automatically. Last step is to set the ‘master’ module to the working condition. The priority level can be set by user in the classic Windows 5-levels style. A simple process administrator is attached in ‘Process/ProcessManagement’ menu.

 

 

 

 

  DOWNLOAD

Robomap Studio

System

Version / Platform / File type / Size

Description

Download

 

 

ROBOMAP Studio full x32

 

 

1:  v1.09102012

4:  v1.09102012

 

Windows 2000, XP, 7, 8 - 32bit / ZIP file / 295 MB

 

 

RobomapStudio (RS) full version

 

 

Data files Converters, Data files Viewers, CAD-like vector-Map Builders, Two universal 2DLS Simulators – small and large maps, Automatic 2DLS scan generation using CSV/TXT pose data in

vector map,  Start Pose Estimators, Continual localization,

Gradient and Evolutionary Cascaded Pose Estimators, Global localization, Simultaneous Localization and Mapping – vector

gSLAM, SLAM with cascaded estimator, Semi-Semantic

Classification of a Known Environment, N-dimensional

non-scalable EA computations, available optimizers: SGA, aGA, MonteCarlo, DE, JADE, JDE, PSO, RPSO, pureCMA-ES, simulator contains 67 benchmark functions, Extended noise maker with fixed or percentage share of selected band-width,

AutoPriority Scheduler for bulk data processing, Process Management, AutoSave Abilities, Output Statistics, Data format suitable for MS Excel, latest gSLAM source code, pureCMA-ES

C++/CLI source code, several examples of the gSLAM, continual

and global localization, user manual.

 

‘ROBOMAP Studio - Subsidiary Tools’ is necessary for all

2DLS simulators for Windows 32bit and 64bit. (RS) VMWare

image contains “(RS) x32” and all necessary tools ready to

run + complete data repository and examples.

 

 

 

1:  Download

4:  Download

 

 

ROBOMAP Studio full x64

 

1:  v1.09102012

4:  v1.09102012

 

Windows XP, 7, 8 - 64bit / ZIP file / 295 MB

 

 

 

1:  Download

4:  Download

 

 

ROBOMAP Studio full x32

(RS) ready to run

Complete system + examples

 

1. VMWare 7,8,9,10.xx Image for

Windows and Linux (2.11 GB)

 

2. VMWare 12 image for Win 7, 8 and 10 (9 GB)

 

Free VMWare Player

for Windows and Linux

 

If you want to use the latest version of the (RS), please, download the “(RS) full x32” and rewrite by it the older (maybe) version in the VMWare image.

 

1:  v1.09102012

 

Windows XP, Vista, 7, 8, Linux

32+64bit / RAR file / 2.11 GB

 

Windows 7, 8, 10 + Linux

32+64bit / RAR file / 9 GB

 

*tested: Fedora, RedHat, Debian, Ubuntu, SuSe, Mandriva

 

 

 

 

 

 

 

1:  Download

 

1:  Download

 

linux.jpg

LINUX

windows.jpg

WINDOWS

Data processing tool

Navigation data

1:  v1.09102012

4:  v1.09102012

Windows XP 32 bit / ZIP file / 35.2 MB

VBA Script + MS SQL 8.0 based data processing

tool for MS Excel 2007

 

1:  Download

4:  Download

Data processing tool

Data from EA calculation

1: v1.09102012

4: v1.09102012

Windows XP 32 bit / ZIP file / 35.2 MB

VBA Script + MS SQL 8.0 based data processing

tool for MS Excel 2007

 

1:  Download

4:  Download

 

 

ROBOMAP Studio

Subsidiary Tools

 

1:  v1.09102012

4:  v1.09102012

 

Windows 32 bit, 64bit / ZIP file / 1.32 GB

 

 

All necessary prerequisites for Windows 32bit and 64bit.

Windows Installer 3.1, .NET libraries 2.0+3.5 SP1, SlimDX v2.0 March 2011, MS Visual Studio 2008 redistributable package SP1, NMath 5.2 numerical library + some useful sw.

 

 

1:  Download

4:  Download

 

 

 

 

 

 

ROBOMAP Studio - gSLAM

‘gSLAM source code

GNU license FREE

 

1:  v 1.02092011

4:  v 1.02092011

Windows XP 32 bit / ZIP file / 137.5 KB

Simultaneous Localization and Mapping (Geometric SLAM).

Source Code for MS VS C++/CLI 2008 SP1 (.Net 3.5 SP1)

Source Code depends on correct (RS) main directory structure – i.e. BMP, RTF, ICO files, Windows registry information, main CFG file etc. You have to download (RS) full version and to install all subsidiary files first !!!

 

1:  Download

4:  Download

 

 

ROBOMAP Studio full

Complete source code

GNU license

 

1:  v1.09102012

4:  v1.09102012

Windows / ZIP file / 19.7MB

 

Complete Source Code for MS-VS-2008-SP1 C++/CLI

Source Code depends on correct (RS) main directory structure – i.e. BMP, RTF, ICO files, Windows registry information, main CFG file etc. You have to download (RS) full version and to install all subsidiary files first !!!

 

 

 

1:  Download

4:  Download

 

 

 

 

Key: (1: primary site, 2, 3, 4, 5  mirror sites), (RS) uses  1: ‘uloz.to’ , 2: ‘minus.com’ , 3: ‘drive.google.com’ , 4: ‘onedrive.live.com’, 5: ‘copy.com’  free cloud data storage services. There is no 24x7 guarantee. Maybe it will work. Keep smile and be happy - life is short :-) .  At maintenance time, primary site will be renewed as the first and will be unattainable. The Primary site ‘uloz.to’ will contain up-to-date version of the (RS) x32 system only !!!. (RS) is free project. If you need any changes or adds-on, you have to pay for it :-) - money talks.ROBOMAP Studio  full x32, x64’ are single threaded applications.

Recipe how to download a file from uloz.to cloud see the instructions below.  (Source1:)

 

 

 

Data Repository

Description

Content

Download

 

Data from real 2DLS Sick PLS100 Sick gmbh, 361beams/180°

Complete package + adds-on something.

133.60 MBytes

 

1:  v 1.10112011

4:  v 1.10112011

 

13 common office environments built-up by paper cardboard boxes, LOG files, PLB map, LSB data, screenshots, LAY files. No odometry data.

 

 

 

1:  Download

4:  Download

 

 

Data from real 2DLS Sick PLS100 Sick gmbh, 361beams/180°

Global Localization experiments

Continual Localization experiments

3.40 MBytes

 

1:  v 1.10112011

4:  v 1.10112011

 

4 common office environments built-up by paper cardboard boxes, PLB map, LSB data, screenshots.

No odometry data.

 

 

 

1:  Download

4:  Download

 

 

 

Data from RADISH repository. Selected large environments.

51.40 MBytes

 

1:  v 1.10112011

4:  v 1.10112011

 

Selected large environments, not very suitable for (RS) geometric SLAM. Without PLB files. LSB data only. PLB ‘reticle’ (frame) must be created in (RS).

http://cres.usc.edu/radishrepository/view-all.php

 

 

 

1:  Download

4:  Download

 

 

 

 

Data from real 2DLS Sick PLS100 Sick gmbh, 361beams/180°

Data suitable for SLAM experiments with correct pose estimator setting.

41.01 MBytes

 

1:  v 1.05122011

4:  v 1.05122011

 

6 simple and common office environments with suitable estimator setting.

PLB ‘reticle’, LSB data, screenshots, estimated path, messages, solved examples.

 

bonn scrn_MO SO.jpgfinal map empty4.jpgchaos1scrn_MO SO.jpg

blud2.JPGkrab2.jpgchodba2 framescrn_MO SO.jpg

Nepojmenovaný.jpg

 

 

 

 

1:  Download

4:  Download

 

Data from 2DLS Sick PLS100 was obtained in environment built-up by classic paper cardboard boxes with different dimensions.

 

 

 

ROBOMAP Studio (v1.0) Copyright © 2011 J.Moravec

Contributors: S.K. Mishra, Petr Pošík

 

‚ROBOMAP Studio’ software is distributed WITHOUT ANY WARRANTY.

 

ROBOMAP Studio is GNU (General Public License) and is free software.

SLAM source code (gSLAM algorithm) of the ‘ROBOMAP Studio’ is GNU (General Public License) and is free software.

 

You can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>.

 

THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM “AS IS” WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.

 

IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.

 

Because (RS) is absolutely free you can do with it anything you want. For example you can throw it to trash or you can use it as a beer mat.

 

 

(RS) version detection

Deployment and installation of the RobomapStudio parts:

All versions have ID_number in main (RS) directory. Something like _RSv1.20112011 alias _RSv#.DDMMYYY, where # is actual version, DDMMYYY is day of the month(DD), month(MM) and year(YYYY) of last update (date in European format).

(RS) is divided into several standalone parts with one main exe module.  All standalone modules need (RS) directory structure and all RTF, BMP etc. files, included to this directory structure. Main (RS) module and all standalone modules have identical name ‘ROBOMAP.EXE’ because of the simple priority scheduler is used instead of a classic job scheduler. Correct deployment of these files is important. Every standalone module can run without existence of the main module or any other module(s).

(RS) Installation instruction

Subsidiary tools required for RobomapStudio x32 for Windows XP 32bit:

ROBOMAP Studio has no full installer at this time. Follow these instructions:

 

0.  Install all subsidiary tools. If it is necessary.

1. Create suitable directory manually ... 'C:\ROBOMAP' for example (it is recommended).

2. Copy content of ZIPpped file to the directory - 'C:\ROBOMAP'.

3. Run Install.exe file in 'C:\ROBOMAP' directory.

4. Select ROBOMAP working directory - 'C:\ROBOMAP' for example (it is recommended).

5. Select visualization tool. Matlab is recommended.

'C:\Program Files\MatlabR2010\bin\matlab.exe' for example.

6. Enable digitizer HP7475A, this setting enables to create and to export the new geometric maps.

7. Press 'INSTALL' button – and hope.

8. (RS) main working window(s) resolution can be changed in menu

(RS):  [Edit\Convert]  \  [EditConfigDataFile]

 

Recommended monitor resolution is 1680x1050. 

RobomapStudio  ALL versions  require minimally Windows XP 32bit SP2 (installation sequence may be important):

 

 

1/ MS Installer 3.1 or higher(according to the Windows version)

2/ .NET2.0 library +.NET2.0 library Service Pack 2 (base package)

3/ .NET3.5 library + .NET3.5 library SP1

4/ SlimDX SDK library 2.xx, March 2011 (must be installed first)*

5/ SlimDX SDK library, September 2011

6/ MS VC++ 2008 SP1 redistributable package.

7/ MS VC++ 2010 SP1 redistributable package (required by NMath 5.2)

8/ Matlab version 5.0 or higher. (v.2009 was tested OK)

9/ NMath library 5.2 for Win x32,x64, XP,Vista,7,8 + use StudentLicenseKey

 

All components (subsidiary tools) must be installed manually. See ‘SubsidiaryTools’ Readme.txt file for more detailed information.

 

*(RS) uses some DLLs from SlimDX March 2011 and some from September 2011. So you need both versions. If 64bit Windows is concerned, .NET 4.0 Full version have to be installed, Client Profile version only is not enough. SlimDX SDK is required as well. By the way, (RS) uses ‘comma’ as a decimal separator. Some Windows - US versions use dot. To correct this problem, you have to change local setting in windows ControlPanel folder: LocalAndLanguagesSettings.

 

ROBOMAP Studio - Function List (Menu system)

[00.00.01] File

 

[00.01.01] File / CreateProjectDescription

[00.02.01] File / Exit

 

[00.00.02] Edit/Convert

 

[00.01.02] Edit/Convert / Edit Config Data File

[00.02.02] Edit/Convert / Convert Laser Data to LSB

[00.03.02] Edit/Convert / Edit PLT File (Run PlotMaker2.2 CZE)

[00.04.02] Edit/Convert / Edit PLT File (Run PlotMaker9.0 ENG)

[00.05.02] Edit/Convert / StartPoses Edit

 

[00.00.03] View/Create

 

[00.01.03] View/Create / View LOG file / Create PLB, LSB, LS1

[00.02.03] View/Create / View PLT file (PlotMaker2.2) / Create PLB map

[00.03.03] View/Create / View CSV, TXT / Create PLB, BIN

[00.04.03] View/Create / Create LS1 scan from PLB model / PLB, LS3

[00.05.03] View/Create / Create LS Simulation ( Mouse, Keyb, Tablet )

[00.06.03] View/Create / 2D LS Simulator (Vector)( GamePad )

[00.07.03] View/Create / 2D LS Simulator (Bitmap)( GamePad )

[00.08.03] View/Create / Create Noisy LSB

[00.09.03] View/Create / View LSB file / Create PLB, LSB, LS1

[00.10.03] View/Create / View PLB file (map of environment)

[00.11.03] View/Create / View LS1 file (one scan)

[00.12.03] View/Create / View PTH file (data from localization)

[00.13.03] View/Create / View VRX file (data from global localization)

[00.14.03] View/Create / View GAB file (data to GA searching)

[00.15.03] View/Create / Compare two scans, LS3 and LS1

 

[00.00.04] ComputeStartPose 

 

[00.01.04] ComputeStartPose / Compute position by hand

[00.02.04] ComputeStartPose / Compute Start Position 1 (1pass,BruteForce,Visual)

[00.03.04] ComputeStartPose / Compute Start Position 2 (2pass,BruteForce)

[00.04.04] ComputeStartPose / Compute Start Position COX 1 (BruteForce,Visual)

 

[00.00.05] ContinualLocalization

 

[00.01.05] ContinualLocalization / Continual Localization 1 (Brute force)

[00.02.05] ContinualLocalization / Continual Localization 2 (HillClimbing)

[00.03.05] ContinualLocalization / Continual Localizaion SGA/aGA 1

[00.04.05] ContinualLocalization / Continual Localization PSO 1

[00.05.05] ContinualLocalization / Continual Localization RPSO 1

[00.06.05] ContinualLocalization / Continual Localization DE 1

[00.07.05] ContinualLocalization / Continual Localization JADE (2D/3D)

[00.08.05] ContinualLocalization / Continual Localization jDE (2D/3D)

[00.09.05] ContinualLocalization / Continual Localization DE 2 (3D)

[00.10.05] ContinualLocalization / Continual Localization COX

 

[00.00.06] CascadedEstimators

 

[00.01.06] CascadedEstimators / Gradient F1,2,3 (CL1+CL2+COX)

[00.02.06] CascadedEstimators / EA + F1,2,3

 

 

[00.00.07] GlobalLocalization

 

[00.01.07] GlobalLocalization / Global Localization 1 (Brute Force)

[00.02.07] GlobalLocalization / Global Localization SGA/aGA 1

[00.03.07] GlobalLocalization / Global Localization PSO/RPSO 1

[00.04.07] GlobalLocalization / Global Localization DE 1 (2D)

[00.05.07] GlobalLocalization / Global Localization DE 2 (3D)

[00.06.07] GlobalLocalization / Global Localization DE 3 (6D)

[00.07.07] GlobalLocalization / Global Localization CMAES 1 (2D)

[00.08.07] GlobalLocalization / Global Localization COX BF 1

[00.09.07] GlobalLocalization / Global Localization COX SGA/aGA 1

[00.10.07] GlobalLocalization / Global Localization COX DE 1

[00.11.07] GlobalLocalization / Global Localization COX PSO/RPSO 1

 

[00.00.08] MapBuilding

 

[00.01.08] MapBuilding / Map Building Simple (Vector) - Geometric SLAM

[00.02.08] MapBuilding / Map Building (Vector)

 

[01.02.08] MapBuilding / Map Building (Vector) / Map Building F3+Vector+EA+subframe

[02.02.08] MapBuilding / Map Building (Vector) / Map Building F3+Vector+EA full

[03.02.08] MapBuilding / Map Building (Vector) / Map Building COX+DE+subframe

[04.02.08] MapBuilding / Map Building (Vector) / Map Building COX+DE full

[05.02.08] MapBuilding / Map Building (Vector) / Line Map Building (Crowley) [not accessible]

[06.02.08] MapBuilding / Map Building (Vector) / LineFitting

 

[00.03.08] MapBuilding / Map Building (Bitmap)

 

[01.03.08] MapBuilding / Map Building (Bitmap) / Map Building (1/0 Occupancy Grid) [incomplete]

[02.03.08] MapBuilding / Map Building (Bitmap) / Map Building (CEE, 1/0 Occupancy Grid) [incomplete]

 

[00.04.08] MapBuilding / Map Building (BF+SubmapBinding)

 

[00.00.09] Semantic

 

[00.01.09] Semantic / Semi-Semantic Classification of a Known Environment

 

[00.00.10] EvolutionaryAlgorithms

 

[00.01.10] EvolutionaryAlgorithms / SGA N-dimensional

[00.02.10] EvolutionaryAlgorithms / aGA N-dimensional

[00.03.10] EvolutionaryAlgorithms / DE N-dimensional

[00.04.10] EvolutionaryAlgorithms / JADE N-dimensional

[00.05.10] EvolutionaryAlgorithms / JADE N-dimensional

[00.06.10] EvolutionaryAlgorithms / SPDE N-dimensional

[00.07.10] EvolutionaryAlgorithms / PSO/RPSO N-dimensional

[00.08.10] EvolutionaryAlgorithms / CMAES N-dimensional

[00.09.10] EvolutionaryAlgorithms / SGA/aGA Optimizer ( dim 2 )

[00.10.10] EvolutionaryAlgorithms / PSO/RPSO Optimizer ( dim 2 )

[00.11.10] EvolutionaryAlgorithms / EEv N-Dimensional [incomplete]

 

[00.00.11] Process

 

[00.01.11] Process / Process Management

 

[00.00.12] Help

 

Algorithms marked as “[incomplete]” (alias gray colored) are not finished yet and can be unstable.

 

  SUBSIDIARY TOOLS LOCATION 

Subsidiary Tools

System

Platform

Link

Status

Microsoft .NET 2.0

Windows XP

http://www.microsoft.com/download/en/details.aspx?id=19

Free

Microsoft .NET 2.0 SP2

Windows XP

http://www.microsoft.com/download/en/details.aspx?id=1639

Free

Microsoft .NET 3.5

Windows XP

http://www.microsoft.com/download/en/details.aspx?id=21

Free

Microsoft .NET 3.5 SP1

Windows XP

http://www.microsoft.com/download/en/details.aspx?id=22

Free

Windows Installer 3.1

Windows XP

http://www.microsoft.com/download/en/details.aspx?id=25

Free

SlimDX SDK 2.0 March 2011

Windows XP, Vista, 7, 8

http://slimdx.org/download.php

Free

Microsoft Visual C++ 2008 SP1

Redistributable Package

Windows XP, Vista, 7, 8

http://www.microsoft.com/download/en/details.aspx?id=5582

Free

Microsoft Visual C++ 2010 Redistributable Package

Windows XP, Vista, 7, 8

http://www.microsoft.com/en-us/download/details.aspx?id=5555

http://www.microsoft.com/en-us/download/details.aspx?id=14632

Free

Matlab - Student version

Windows XP, Vista, 7, 8

http://www.mathworks.com/products/matlab/tryit_b.html

http://www.mathworks.com/academia/student_version/faq/index.html

Free

Octave

Windows XP, Vista, 7, 8

http://www.gnu.org/software/octave/

http://www.gnu.org/software/octave/download.html

Free

AutoCAD

Windows XP, Vista, 7, 8

http://www.autodesk.com

Not Free

ABViewer 7

Windows XP, Vista, 7, 8

http://www.cadsofttools.com/

http://www.slunecnice.cz/sw/abviewer/

Not Free

ArchiCAD

Windows XP, Vista, 7, 8

http://www.graphisoft.com/products/archicad/

Not Free

Iridium - Math.NET Numerics

Windows XP, Vista, 7, 8

http://www.mathdotnet.com/Iridium.aspx

Free

Center Space NMath Library

Windows XP, Vista, 7, 8

http://www.centerspace.net/products/nmath/

Not Free

VMWare Workstation

Windows XP, Vista, 7, 8

www.vmware.com

Not Free

VMWare Player

Windows XP, Vista, 7, 8

www.vmware.com

Free

 

 

 

 

 

 

    SCREENSHOTS    

 

 

Global localization, three dimensional problem, DE optimizer

Map of Environment Viewer - Wesley Woods geriatric Hospital Clifton USA

GL DE 3D.jpg

PTL.jpg

N-dimensional optimization, RPSO optimizer, Ackley’s path function

SLAM – Cox’s pose estimator is used

EA ndim RPSO .jpg

COX SLAM.jpg

2DLaser Simulator (Vector); Keyboard + Mouse + Tablet Mode

SLAM – evolutionary F3 estimator is used (Differential evolution)

Nepojmenovaný.jpg

Nepojmenovaný.jpg

2DLaser Simulator (Vector); II. Generation – GamePad + JoyStick

The result of classification - Viewer – Find correct pose in environment

Nepojmenovaný.jpg

Nepojmenovaný.jpg

VRX file visualization – Level viewer

LOG File Viewer & Converter

Nepojmenovaný.jpg

LOG.jpg

N-dimensional optimization, DE optimizer, Michalewicz's function

N-dimensional optimization, SGA optimizer

DE.jpg

SGA.jpg

Noise simulator

Scan Comparator

noise.jpg

Scan comparator.jpg

2pass, BruteForce Global Robot Localization

Precise Start Pose Estimator with visualization

2pass.jpg

start.jpg

Continual Localization – DE; estimated path

Continual Localization – DE; results

1 Nepojmenovaný.jpg

2 Nepojmenovaný.jpg

Global localization; DE 3Dim optimization problem; POP=GEN=300;10x10m

Continual Localization in Known environment

Nepojmenovaný.jpg

Nepojmenovaný.bmp

2DLaser Simulator (Bitmap); II. Generation – GamePad + JoyStick

PTH File Viewer; result of the SLAM process; memorized positions

Nepojmenovaný.bmp

Nepojmenovaný.bmp

N-dimensional optimization, DE optimizer, DeJong's function

N-dimensional optimization, RPSO optimizer, Rastrigin's function

o.gif

rastrigin.gif

Two Dimensional Cascaded Evolutionary Estimator - DE optimizer

Simple Scan Generator

cas.bmp

scan.bmp

Semi-Semantic Classification of a Known Environment – Defining Hyperplane

Semi-Semantic Classification of a Known Environment – 2D Peak Classification

Semantic 1.jpg

Semantic 2.jpg

Continual localization F1,2,3 Estimators, 3Dim JADE optimizer, large environments

Continual localization F1,2,3 Estimators, 2Dim JADE optimizer, large environments

obr1.bmp

obr2.bmp

 

 

 

 

 

 

 

  INTERESTING LINKS 

ROBOTICS AREA

 

 

 

 

OPENSLAM  - SLAM algorithms database etc.

www.openslam.org

 

Robot Operating System WEB site

http://www.ros.org/wiki/

 

Czech Republic - robotika WEB

http://robotika.cz/

 

 

 

 

Dieter Fox

‘Probabilistic Robotics’, localization, SLAM, 2D,3D

http://www.cs.washington.edu/homes/fox/

 

Sebastian Thrun

‘Probabilistic Robotics’, localization, SLAM, 2D,3D

http://robots.stanford.edu/

 

Cyrill Stachniss

Database – repository, SLAM, robotics

http://www.informatik.uni-freiburg.de/~stachnis/papers.html

 

Carmen SW

Carnegie Mellon Robot Navigation Toolkit

http://carmen.sourceforge.net/home.html   http://carmen.sourceforge.net/home.html

 

Tim Bailey

SLAM, Kalman Filter, general survey

http://www-personal.acfr.usyd.edu.au/tbailey/

 

Kai Arras

SLAM, Kalman Filter, general survey

The CAS Robot Navigation Toolbox

http://www.informatik.uni-freiburg.de/~arras/

 

Andrzej Pronobis

Semantic Mapping / Semantic Annotation of Space

http://www.pronobis.pro/home

 

 

Arthur Guez

SLAM

http://www.cs.mcgill.ca/~aguez/

 

Kris Beevers

SLAM

http://www.cs.rpi.edu/~beevek/

 

Chieh-Chih (Bob) Wang

SLAM

http://www.csie.ntu.edu.tw/~bobwang/

 

Luz Abril Torres-Méndez

Visual navigation

http://www.cim.mcgill.ca/~latorres/

 

Gregory Dudek - robotics

http://www.cim.mcgill.ca/~dudek/

 

Albert Diosi

SLAM

http://www.irrc.monash.edu.au/adiosi/index.html

 

Dorit Borrmann

6D SLAM

http://www-lehre.inf.uos.de/~dborrman/

 

IIIT India – robotics laboratory

http://www.iiit.net/

http://robotics.iiit.ac.in/

 

University Carlos III

Madrid, Spain

Moreno, Munoz, Blanco, Garrido

http://roboticslab.uc3m.es/roboticslab/

 

Marco Porta

Visual robotics

http://vision.unipv.it/people/porta/research.html

 

Miguel Torres Torriti

PONTIFICIA UNIVERSIDAD CATOLICA DE CHILE

Robotics laboratory - Spain

robotics

http://ral.ing.puc.cl/

http://web.ing.puc.cl/~mtorrest/index.htm

 

Michael Milford

RAT SLAM

http://itee.uq.edu.au/~milford/

 

Mike Bosse, CSIRO

SLAM

http://research.ict.csiro.au/

http://www.ict.csiro.au/staff/mike.bosse/

 

Damien P. George

SLAM

http://dpgeorge.net/

 

ParisTech

CoreBots, CoreSLAM

http://www.mines-paristech.eu/Researcher/Fields-of-Research/Mathematics-and-systems/CRI/

http://corebots.net/menuresources.html?8259bfafdad155ffd590c45f4fa21fb6=fc5dce8e0eaaa762aa43096c2336ffc4

 

Samuel T. Pfister – California Institute of Technology

SLAM

http://robotics.caltech.edu/~sam/

 

Andrzej Pronobis

http://www.pronobis.pro/home

 

Jose A. Castellanos

SLAM, 2D,3D Lasr, Vision, Line segmentation

http://webdiis.unizar.es/~joseac/Home.html

 

Juan Domingo Tardós

6DOF SLAM,2D,3D Laser, SLAM, Line Segmentation, Vision

http://webdiis.unizar.es/~jdtardos/publications.html

http://webdiis.unizar.es/~jdtardos/

 

Jason O'Kane, general robotics

cse.sc.edu/~jokane/

 

IEPF algorithm DEMO

http://cgm.cs.mcgill.ca/~godfried/teaching/projects97/guirlyn/iterEndPoints/frames.html

 

Richard O. Duda, IEPF and Line Tracking algorithm

Richard O. Duda and Peter E. Hart. Pattern Classification and Scene Analysis. Wiley-Interscience, 1976.

http://www.ai.sri.com/pubs/search.php?id=181

 

Alexander Gelbukh, Sulema Torres, Itzamá López (Eds.)

Congres on Computations

http://prometeo.cic.ipn.mx/2006/cd/

 

John J. Leonard

SLAM, localization, navigation

http://groups.csail.mit.edu/marine/wiki/index.php?title=Main_Page

http://oe.mit.edu/~jleonard

 

Interesting SLAM paper repository

http://www.cas.kth.se/SLAM/slam-papers.html

 

Henrik I. Christensen

General robotics

http://www.hichristensen.net/

http://www.nada.kth.se/~hic/

http://en.wikipedia.org/wiki/Henrik_I._Christensen

 

COLD Database

http://cogvis.nada.kth.se/COLD/

 

Patric Jensfelt

http://www.csc.kth.se/~patric/

 

Cognitive Maps

http://www.cognitivemap.net/

 

Cognitive Maps

http://www.aut.ac.nz/research/research-institutes/cair/robotics

 

Robot Operating System

http://www.ros.org/wiki/

 

RobotVisionGroup

http://www2.imperial.ac.uk/robotvision/

 

Steven Lovegrove

Real-time Spherical Mosaicing Using Whole Image Alignment

http://www.doc.ic.ac.uk/~sl203/?id=1

 

Robo Vision

http://www.roborealm.com/links/vision_software.php

 

OpenSource Bayesian Filtering Classes

http://bayesclasses.sourceforge.net/Bayes++.html

 

Christian Doppler Laboratory, SLAM

http://www.cvpapers.com/rr.html

 

Kristopher R. Beevers

http://www.cs.rpi.edu/~beevek/thesis/

 

Velodyne SLAM - Dataset

http://www.mrt.kit.edu/z/publ/download/velodyneslam/dataset.html

 

Kurt Konolige, SLAM

http://pub1.willowgarage.com/~konolige/

http://www.ai.sri.com/people/konolige

 

Point Cloud Library

http://www.pointclouds.org/

 

Willow Garage

http://www.willowgarage.com/

 

ARC Centre of Excellence for Autonomous Systems, University Of Sydney Australia

http://www.cas.edu.au/home.html

 

Clustering algorithms

http://home.dei.polimi.it/matteucc/Clustering/tutorial_html/index.html

 

Karto Robotics SLAM

http://www.kartorobotics.com/

 

Idaho National laboratory

https://inlportal.inl.gov/portal/server.pt?open=512&objID=455&parentname=CommunityPage&parentid=6&mode=2

 

Radu B. Rusu

http://rbrusu.com/research

 

Philippe Fraisse

http://www.lirmm.fr/~fraisse/index.php

 

Wang Han

http://www3.ntu.edu.sg/home/hw/  http://research.ntu.edu.sg/expertise/academicprofile/pages/StaffProfile.aspx?ST_EMAILID=hw

 

Ashutosh Saxena

http://www.cs.cornell.edu/~asaxena/index.php

 

Andrea Censi

http://www.cds.caltech.edu/~ender/index.html

 

Albert Diosi’s small robot platform

http://abcrobotics.com/ , http://diosirobotics.net/

 

FabMAP 2.0 video SLAM

http://www.robots.ox.ac.uk/~mjc/Software.htm

 

Mision Lab sw

http://www.cc.gatech.edu/aimosaic/robot-lab/research/MissionLab/

 

ACT research group

http://act.rasip.fer.hr/groups_amor.php

 

Andrew Comport ‘s visual SLAM

http://www.i3s.unice.fr/~comport/

 

RI CMU bio robotics lab

http://biorobotics.ri.cmu.edu/robots/index.html

 

Oscar Martinez Mozos

http://www.informatik.uni-freiburg.de/~omartine/

 

MMC Lab

http://www.lienhart.de/Prof._Dr._Rainer_Lienhart/Welcome.html

 

Laboratory of Perceptual Robotics MIT

http://www-robotics.cs.umass.edu/index.php/Robots/Robots

 

Robotics and Automation Laboratory,

Pontifica Universidad Catolica de Chile

http://ral.ing.puc.cl/index.htm

 

RRLIB – The Robotics Research Library

http://rrlib.cs.uni-kl.de

http://agrosy.informatik.uni-kl.de/en/

 

Leg Laboratory MIT

http://www.ai.mit.edu/projects/leglab/

 

Nakamura Laboratory

http://www.ynl.t.u-tokyo.ac.jp/

 

SLAM Benchmarking

http://kaspar.informatik.uni-freiburg.de/~slamEvaluation/index.php

 

Artificial Perception for Intelligent Systems and Robotics Institute of Systems and Robotics - University of Coimbra

http://ap.isr.uc.pt/

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

EVOLUTIONARY COMPUTATIONS

 

De Jong's test suite

http://home.ku.edu.tr/~dyuret/pub/aitr1569/node19.html

 

GeatBOX

http://www.geatbx.com,

 

Shubert Benchmark function

http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page1882.htm

 

Test Problems

http://www.math.ntu.edu.tw/~wwang/cola_lab/test_problems/multiple_opt/multiopt_prob/Ackley/Ackley.htm

 

Global Optimization by Repulsive Particle Swarm method

http://www.nehu-economics.info/rpswarm.html

 

SOMA optimizer

http://www.ft.utb.cz/people/zelinka/soma/

 

The Cross-Entropy Toolbox

http://www.maths.uq.edu.au/CEToolBox/

http://iew3.technion.ac.il/CE/

 

Ralf Salomon - publications

http://www.ifi.uzh.ch/~salomon/pubs.html

 

RGA - algorithm for black box global optimization

http://web.ift.uib.no/~antonych/RGA4.html#dixon

 

Rosenbrock Method

http://www.applied-mathematics.net/optimization/rosenbrock.html

 

GEATbx: Genetic and Evolutionary Algorithm Toolbox for use with MATLAB

http://www.pg.gda.pl/~mkwies/dyd/geadocu/index.html

 

PSOVis Particle Swarm Optimization

http://gecco.org.chemie.uni-frankfurt.de/PsoVis/index.html

 

Bukin A.D., (1997), New Minimization Strategy For Non-Smooth Functions, Budker Institute of Nuclear Physics, 1997, Novosibirsk

http://www.inp.nsk.su/activity/preprints/oldwww/texts/p97_79.ps

 

SCI2S Thematic Public Websites

SGA, (DE, OBDE, SaDE, JADE, DEGL, SFSLDE), Simulated Annealing, Memetic Algorithms

http://sci2s.ugr.es/EAMHCO/#LSCOP-special-issue-SOCO

 

A.E. Eiben

Evolutionary computations, Multi-parent recombination, Parameter Control, Parameter Tuning, Artificial Life, Evolutionary Robotics, Evolutionary Art

http://www.cs.vu.nl/~gusz/

 

Janez Brest, jDE

 

http://labraj.uni-mb.si/en/Janez_Brest

 

University of Granada

Global optimization, Souce codes

http://sci2s.ugr.es/EAMHCO/

 

Efrén Mezura-Montes

Global optimization

http://www.lania.mx/~emezura/

 

Josef Tvrdík, Global optimization problems, DE optimization, Matlab libraries, C++ libraries

http://prf.osu.cz/kip/index.php?idc=13362

http://albert.osu.cz/tvrdik/

http://albert.osu.cz/oukip/optimization/

 

António Manso, Genetic algorithms, Multi population genetic algorithms

http://orion.ipt.pt/~manso/

http://orion.ipt.pt/~manso/MUGA_2007/index.htm

 

Stefan Wagner, Global Optimization, HeuristicLAB software

http://heal.heuristiclab.com/team/wagner

 

DeJong K., An analysis of the behavior of a class of genetic adaptive systems, Ph.D. thesis, University of Michigan, 1975

http://home.ku.edu.tr/~dyuret/pub/aitr1569/node19.html

 

Laboratory of Information Processing, Department of Information Technology, Lappeenranta University of Technology, Lappeenranta, Finland

http://www.it.lut.fi/ip/evo/functions/functions.html

 

Pohlheim H., GEATbx.com, genetic and evolutionary algorithm toolbox for Matlab,December 2006

http://www.geatbx.com,

 

Molga M., Smutnicki C.

Test functions for optimization needs

www.zsd.ict.pwr.wroc.pl/files/docs/functions.pdf

 

Shubert Function

http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page1882.htm

 

Ackley D. H., A Connectionist Machine for Genetic Hillclimbing, Kluwer Academic, Publishers, 1987.

http://www.math.ntu.edu.tw/~wwang/cola_lab/test_problems/multiple_opt/multiopt_prob/Ackley/Ackley.htm

 

Mishra S.K., Performance of Differential Evolution and Particle Swarm Methods on Some Relatively Harder Multi-modal Benchmark  functions, Department of Economics, North-Eastern Hill University, Shillong, Meghalaya (India).

http://www.nehu-economics.info/rpswarm.html

 

Zelinka Ivan, Department of Informatics and Artificial Intelligence, Faculty of Applied Informatics, Tomas Bata Univerzity in Zlin

http://www.ft.utb.cz/people/zelinka/soma/

 

Nikos Drakos, Computer Based Learning Unit, University of Leeds, 1993, 1994, 1995, 1996, Ross Moore, Mathematics Department, Macquarie University, Sydney, 1997, 1998, 1999.

Botev Zdravko, Kroese Dirk, Liu Jenny, Nariai Sho, Taimre Thomas, The Cross-Entropy Toolbox, December 17, 2004, The University of Queensland, Australia

http://www.maths.uq.edu.au/CEToolBox/ 

http://iew3.technion.ac.il/CE/

 

Rosenbrock H. H., An Automatic Method for Finding the Greatest or Least Value of a Function, Computer Journal, Vol 3, pp. 175-184, 1960.

http://web.ift.uib.no/~antonych/RGA4.html#dixon

http://www.applied-mathematics.net/optimization/rosenbrock.html

 

Salomon R., Reevaluating genetic algorithm performance under coordinate rotation of benchmark functions, BioSystems, vol. 39, pp. 263-278, 1996.

http://www.ifi.uzh.ch/~salomon/pubs.html

 

Kwiesielewicz M., Technical University of Gdansk, Faculty of Electrical and Control Engineering, Control Engineering Department, G. Narutowicza 11/12, PL-80-952 Gdansk, Poland

http://www.pg.gda.pl/~mkwies/dyd/geadocu/index.html

 

DeCastro L. N., Timmis J., An Artificial Immune Network for Multimodal Function Optimization, Proceedings of IEEE Congress on Evolutionary Computation (CEC'02), vol. 1, pp. 699-674, 2002, May, Hawaii.

http://gecco.org.chemie.uni-frankfurt.de/PsoVis/index.html

 

Bukin A.D., (1997), New Minimization Strategy For Non-Smooth Functions, Budker Institute of Nuclear Physics, 1997, Novosibirsk,

http://www.inp.nsk.su/activity/preprints/oldwww/texts/p97_79.ps

 

University of Tokyo, Hasegawa laboratory

http://beep.c.u-tokyo.ac.jp/index_english/Home.html

 

Classic Benchmark problems

http://www.cs.cmu.edu/afs/cs/project/jair/pub/volume24/ortizboyer05a-tml/node6.html

 

Eric Rollins

Cellular Automata, EA, Parallel Programming

http://www.mindspring.com/~eric_rollins/

 

 

Mark Ebner

EA computations

https://www.math-inf.uni-greifswald.de/mathe/index.php/mitarbeiter/608-prof-marc-ebner

http://www.ra.cs.uni-tuebingen.de/mitarb/ebner/

 

Giovanni Iacca, Compact DE

http://users.jyu.fi/~giiacca/

 

Kimeme Optimization

Software Linux and Windows x32 x64

http://www.kimeme.com

http://cyberdynesoft.it/

 

Evolutionary Optimisation in

Uncertain or Dynamic Environments

http://www.soft-computing.de/ieee_ecidue.html

 

Neural Net(s)

http://neurondotnet.freehostia.com/

http://www.codeproject.com/KB/dotnet/neuralnetwork.aspx

 

University of Amsterodam

http://isla.science.uva.nl/node/1

 

Natural Selection

http://www.natural-selection.com/index.html

 

Nikolaus Hansen

http://www.lri.fr/~hansen/

http://www.sigevo.org/gecco-2010/tutorials.html#ecua

 

C++ evolutionary computation components framework

http://eodev.sourceforge.net/

 

C.I. Lab, PSO resources

http://www.cil.pku.edu.cn/resources/

 

Kanpur Genetic Algorithms Laboratory

http://www.iitk.ac.in/kangal/codes.shtml

 

Daniela Zaharie,DE

http://web.info.uvt.ro/~dzaharie/

 

Qingfu Zhang, DE

http://dces.essex.ac.uk/staff/zhang/

 

The Marulan Datasets, Australian Centre for Field Robotics

http://sdi.acfr.usyd.edu.au/

 

Marco Montes De Oca, Frankenstein’s PSO

http://montes-de-oca.com/publications.html

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

EVOLUTIONARY ROBOTICS

 

Evolutionary robotics main page

http://laral.istc.cnr.it/evorobot/

 

Evolutionary robotics Wikipedia

http://en.wikipedia.org/wiki/Evolutionary_robotics

 

Dario Floreano

http://en.wikipedia.org/wiki/Dario_Floreano

http://lis.epfl.ch/

 

Stefano Nolfi

http://en.wikipedia.org/wiki/Stefano_Nolfi

http://laral.istc.cnr.it/nolfi/

 

Vasant Honavar

http://en.wikipedia.org/wiki/Vasant_Honavar

http://www.cs.iastate.edu/~honavar/

 

Andrew Nelson, Evolutionary Robotics

http://www.nelsonrobotics.org/evolutionary_robotics_web/bibliography.html

 

Craig Reynolds

http://www.red3d.com/cwr/

 

 

 

 

 

 

 

GENERAL INTERESTING LINKS

 

AForge.NET Framework

.NET library, Video capture, Math, ImageProcessing, Neural Networks. FuzzyLogic etc.

http://code.google.com/p/aforge/

 

 

Accord .NET Framework

Extension of AForge.NET Framework

http://accord-net.origo.ethz.ch/

 

Open Asset Import Library

http://assimp.sourceforge.net/

 

Multiple Precision Integers and Rationals

http://mpir.org/

 

The GNU Multiple Precision Arithmetic Library

http://gmplib.org/

 

A GNU Multi-Precision Library for .NET

http://www.emilstefanov.net/Projects/GnuMpDotNet/

 

Computational Geometry: Algorithms and Applications

http://www.cs.uu.nl/geobook/

 

The GNU MPFR Library

http://www.mpfr.org/

 

Wikipedie List of Numerical Libraries

http://en.wikipedia.org/wiki/List_of_numerical_libraries

 

Extreme optimization profi

http://www.extremeoptimization.com/Downloads.aspx

 

Free C/C++ Sources for Numerical Computation

http://cliodhna.cop.uop.edu/hetrick/c-sources.html

 

Open C++ libraries Robotics, SLAM

http://www.cvpapers.com/rr.html

 

SURF algorithm

http://www.vision.ee.ethz.ch/~surf/index.html

 

SIFT Keypoint Detector

http://www.cs.ubc.ca/~lowe/keypoints/

 

.NET Math Library

http://www.mathdotnet.com/About.aspx

 

.NET MS Connect Math Library

http://connect.microsoft.com/VisualStudio/feedback/details/486314/download-the-fft-library-in-the-net-framework

 

Linear Algebra Pack

http://www.netlib.org/lapack/

 

C++ FAQ - How accurate floating point comparison is?

http://www.softwareandfinance.com/CPP/FAQ_Floating_Point.html

 

Why don't floating point comparisons work?

http://prokutfaq.byethost15.com/FloatCompare

 

Comparing floating point numbers

http://www.cygnus-software.com/papers/comparingfloats/Comparing%20floating%20point%20numbers.htm

 

What Every Computer Scientist Should Know About

Floating-Point Arithmetic

http://download.oracle.com/docs/cd/E19957-01/806-3568/ncg_goldberg.html

 

Humanoid walking SW

http://www.vicon.com

 

Carlos Oliveira

http://research.coliveira.net/

 

Eberhard Karls Universität Tübingen

http://www.ra.cs.uni-tuebingen.de/forschung/welcome_e.html

 

HPGL Viewer (PLT Viewer)

http://service-hpglview.web.cern.ch/service-hpglview/

 

Swplot (PLT Viewer)

http://www.swplot.com/splot.htm

 

FPLOT  (PLT Viewer)

http://www.webring.org/l/rd?ring=caduser;id=49;url=http%3A%2F%2Fwww%2Efplot%2Ecom%2F

 

ViewCompanion Pro (PLT Viewer)  

http://www.softwarecompanions.com/vcpro.html

 

ETE Cad (PLT Viewer)

http://www.etecad.com/

 

PloComp (PLT Viewer)

http://www.isoplotec.co.jp/eplocomp.htm

 

AB Viewer (PLT Viewer)

http://www.cadsofttools.com/en/products/abviewer.html

 

Cadviewer (PLT Viewer)

http://www.cadviewer.com/

 

RxView (PLT Viewer)

http://www.rasterex.com/Products/Windows-Viewer.aspx

 

Professor A. D. Marshall

http://www.cs.cf.ac.uk/Dave/

 

Pedestrian Detection Lab.

http://www.pedestrian-detection.com/

 

Daphne Coller

http://ai.stanford.edu/~koller/activities.html

 

Matthew Kusner – lawn mower

http://www.matthewkusner.com/

 

Mitsubishi Electric

Technical Reports related to Machine Learning

http://www.merl.com/publications/?pub_type=Technical+Reports&pub_area=Machine%20Learning

 

Vysoká Škola Báňská – Technická Universita Ostrava

Fakulta Strojní, Katedra Robotechniky

http://robot.vsb.cz/mobilni-roboty/

 

Robot System web

http://www.robotsystem.cz/

 

Jonas Witt, Hamburg University of Technology

http://www.jonaswitt.de/index.shtml

 

AI Online Code repository

http://aima.cs.berkeley.edu/code.html

 

C++ FAQ - How accurate floating point comparison is?

http://www.softwareandfinance.com/CPP/FAQ_Floating_Point.html

 

Why don't floating point comparisons work?

http://prokutfaq.byethost15.com/FloatCompare

 

Comparing floating point numbers

http://www.cygnus-software.com/papers/comparingfloats/Comparing%20floating%20point%20numbers.htm

 

What Every Computer Scientist Should Know About

 Floating-Point Arithmetic

http://download.oracle.com/docs/cd/E19957-01/806-3568/ncg_goldberg.html

 

 

Makerere University School of Computing

http://www.cit.mak.ac.ug/cs/aigroup/index.html

 

Advanced Institute of Science and technology Kaist

http://www.kaist.edu/english/index.php

 

MIT  Robot Locomotion Group

http://groups.csail.mit.edu/locomotion/index.html

 

Jean-Bernard Hayet, CIMAT

http://personal.cimat.mx:8181/~jbhayet/

 

Obotics Courses

http://roboticscourseware.org/

 

VL Feat .org, SIFT, KDTree, SVM etc.

http://www.vlfeat.org/overview/sift.html

 

Open SIFT

http://robwhess.github.io/opensift/

 

ACR

http://www.robots.ox.ac.uk/~vgg/research/affine/

 

MRPT Development in robotics + datasets

http://www.mrpt.org/

http://www.mrpt.org/robotics_datasets

 

Dirk Holz SLAM

http://www.ais.uni-bonn.de/~holz/spmicp/

 

Ph.D. thesis on Evolutionary Multiobjective Optimization

http://delta.cs.cinvestav.mx/~ccoello/EMOO/phdtheses.html

 

Maxon Motors

http://www.maxonmotor.com/

 

CSIRO ICT research Centre

http://www.csiro.au/

 

IEEE floating point ?

http://www.yosefk.com/blog/consistency-how-to-defeat-the-purpose-of-ieee-floating-point.html

 

LRIA laboratories

http://www.lria.usthb.dz/   ,   http://www.usthb.dz/en/

 

Roland Jan Geraerts, Path planning

http://www.staff.science.uu.nl/~gerae101/

 

Jeff Orkin, AI Game Books

http://alumni.media.mit.edu/~jorkin/

 

Online code repository

http://aima.cs.berkeley.edu/code.html

 

NAG library

http://www.nag.co.uk/numeric/CL/CLdescription.asp

 

D. Xiang Bai, Animals shilouettes dataset

http://mc.eistar.net/~xbai/softwares.html

 

THOMSON & REUTERS

SCIENCE CITATION INDEX EXPANDED

http://ip-science.thomsonreuters.com/mjl/publist_sciex.pdf

http://science.thomsonreuters.com/cgi-bin/jrnlst/jlresults.cgi?PC=D&Alpha=I

 

Web of Science

http://images.webofknowledge.com/WOK46/help/WOS/

 

SCOPUS index

http://www.elsevier.com/online-tools/scopus/content-overview

https://files.sciverse.com/documents/xlsx/title_list.xlsx

https://www.cder.dz/spip.php?article1510

 

Cite Factor List

http://www.scijournal.org/

http://www.citefactor.org/journal-impact-factor-list-2014.html

http://www.omicsonline.org/open-access-journals-impact-factors.php?gclid=CInLneiPmM4CFYU_GwodHHYIiA

 

SCIMAGO, Scimago Journal & Country Rank

http://www.scimagojr.com/

 

Top Journals for Computer Science and Electronics

http://www.guide2research.com/journals/

http://www.guide2research.com/journals/list-2015.pdf

 

CitEc

http://citec.repec.org/

 

Some journals, EA

http://www.macs.hw.ac.uk/~ml355/journals.htm

 

Taylor Francis

http://explore.tandfonline.com/page/est/ect-impact-factors

 

Scientific result definition

http://www.vyzkum.cz/FrontClanek.aspx?idsekce=29415

 

Top Journals for Computer Science and Electronics

http://www.guide2research.com/journals/

http://www.guide2research.com/journals/list-2015.pdf

 

Springer impacted journals

http://www.springer.com/computer/impact+factor+journals+computer+science?SGWID=0-1743318-12-863108-0

 

Open Access Journals Impact Factor List

http://www.omicsonline.org/open-access-journals-impact-factors.php?gclid=CIb25bXdhs0CFRYTGwodCHYM1w

 

 

 

 

 

 

 

 

 

 

 

 

 

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RobomapStudio is distributed with the support of the University of Freiburg, Dept. of Computer Science

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  PUBLICATIONS 

        Journal Papers

 

 

·          Moravec J. (2015). A Comparative Study: L1-norm vs. L2-norm, point-to-point vs. point-to-line Metric, Evolutionary Computation vs. Gradient Search, Applied Artificial Intelligence, vol. 29, no. 2, pp. 164 – 210

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·          Moravec J., Pošík P. (2014). Global Robot Localization Under Noise Stress Utilizing EA Methods and Semi-semantic Classification of a Known Environment, Applied Artificial Intelligence, vol. 28, no. 4, pp. 360 - 417

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·          Moravec J., Pošík P. (2014). A Comparative Study: The Effect of the Perturbation Vector Type in the Differential Evolution Algorithm on the Accuracy of Robot Pose and Heading Estimation, Evolutionary Intelligence Journal, vol. 6, no. 3, pp. 171-191   

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·          Moravec J., (2012). Map Building of Unknown Environment Using L1-norm, Point-to-Point Metric and Evolutionary Computation, Polibits - Research Journal on Computer Science and Computer Engineering with Applications, vol. 46, pp. 29-38

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·          Moravec J., (2012). Cascaded Evolutionary Estimator for Robot Localization, International Journal of Applied Evolutionary Computation, vol. 3, no. 3, pp. 33-61

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·          Moravec J., (2000). Single-chip Multi-Processor Communication With PC, Sdělovací Technika, vol. 48, no. 11

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        Conference Papers

 

 

 

·         Moravec J., (2001). Continuous Robot Localization in Known Environment Using Genetic Algorithms, The 10th IEEE International Conference on Fuzzy Systems FUZZ IEEE 2001, Melbourne, Australia, p.6 (poster)

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·         Moravec J., Přeučil, L., (2001). Map Building of Unknown Environment Based on Laser Range Finder, 3rd International Conference on Mechatronics and Biomechanics 2001, Třešť, pp. 221-228, ISBN 80-01-0235-4, University of Brno, Institute of Solid Mechanics

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        Workshop Papers

 

 

 

·         Moravec J., (2002). Robot Localization using Genetic Algorithms, Proceedings of The CTU Workshop 2002, p. 3, ISBN 80-01-02511-X

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·         Moravec J., Přeučil, L., (2001). Advanced Approach to Sensor Data Processing for Autonomous Systems, CTU Workshop 2001, vol. A, p. 2, ISBN 80-01-02335-4

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·         Moravec J., Přeučil, L., (2001). A Novel Approach To Accurate Mobile Robot Positioning, Poster 2001, The 5th International Student Conference on Electrical Engineering, CTU Poster 2001, p.30, Prague

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Technical Reports

 

 

 

·         Moravec J., Přeučil, L., (2001). Movement and Continual Localization in Known Environment, Technical Report, CTU GLR 59/01, p.12

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·         Moravec J., Přeučil, L., (2001). Methods of Mobile Robot Positioning in Known Environment, Technical Report, CTU GLČ 52/00, p.18

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·         Moravec J., Přeučil, L., (2000). Advanced Methods of Sensorial Data Processing and Way of a Known Environment Representation in Autonomous Mobile Systems, Technical Report, CTU 2000, p.6

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        Theses

 

 

 

 

 

·         Moravec J., (2014). Evolutionary Algorithms in Mobile Robotics, PhD Thesis, Czech Technical University in Prague, Faculty of Electrical Engineering, Department of Cybernetics, IMR Group, p. 331

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   CZE    ENG

 

·         Moravec J., (2002). Methods of Robot Localization in Indoor Environment, PhD Thesis – obligatory minimum, Czech Technical University in Prague, Faculty of Electrical Engineering, Department of Cybernetics, IMR Group, p. 44

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 ENG

 

·         Moravec J., (1998). Selected Applications in Area of Construction and Operation of Astronomical Telescopes, Master Thesis, West Bohemia University, Faculty of Applied Sciences, Department of Cybernetics, p. 196

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 CZE

 

·         Moravec J., (1992) Programmer Libraries: Scanty Basic, SPS Nové Město nad Metují, p. 243

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 CZE

 

 

 

 

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