scholarly journals Coupling Transparency and Visibility: a Translucent Middleware Approach for Positioning System Integration and Management (PoSIM)

2006 ◽  
Author(s):  
Paolo Bellavista ◽  
Antonio Corradi ◽  
Carlo Giannelli
Keyword(s):  
System Integration ◽  
Positioning System

scholarly journals MAPPING AND POSITIONING SYSTEM ON OMNIDIRECTIONAL ROBOT USING SIMULTANEOUS LOCALIZATION AND MAPPING (SLAM) METHOD BASED ON LIDAR

2021 ◽  
Vol 83 (6) ◽  
pp. 41-52
Author(s):  
Achmad Akmal Fikri ◽  
Lilik Anifah
Keyword(s):  
Monte Carlo ◽  
System Integration ◽  
Simultaneous Localization And Mapping ◽  
Autonomous Robot ◽  
Positioning System ◽  
Adaptive Monte Carlo ◽  
Surrounding Environment ◽  
Localization And Mapping ◽  
Mapping System ◽  
Monte Carlo Localization

The main problem from autonomous robot for navigation is how the robot able to recognize the surrounding environment and know this position. These problems make this research weakness and become a challenge for further research. Therefore, this research focuses on designing a mapping and positioning system using Simultaneous Localization and Mapping (SLAM) method which is implemented on an omnidirectional robot using a LiDAR sensor. The proposes of this research  are mapping system using the google cartographer algorithm combined with the eulerdometry method, eulerdometry is a combination of odometry and euler orientation from IMU sensor, while the positioning system uses the Adaptive Monte Carlo Localization (AMCL) method combined with the eulerdometry method. Testing is carried out by testing the system five times from each system, besides that testing is also carried out at each stage, testing on each sensor used such as the IMU and LiDAR sensors, and testing on system integration, including the eulerdometry method, mapping system and positioning system. The results on the mapping system showed optimal results, even though there was still noise in the results of the maps created, while the positioning system test got an average RMSE value from each map created of 278.55 mm on the x-axis, 207.37 mm on the y-axis, and 4.28o on the orientation robot.

Integration of Satellite and Inertial Positioning Systems

1990 ◽  
Vol 43 (1) ◽  
pp. 48-57 ◽  
Author(s):  
M. Napier
Keyword(s):  
Global Positioning System ◽  
System Integration ◽  
System Performance ◽  
Inertial Navigation ◽  
Positioning System ◽  
Navigation Systems ◽  
Relative Positioning ◽  
Inertial Navigation Systems ◽  
Positioning Systems ◽  
Global Positioning

The Global Positioning System (GPS) offers an absolute positioning accuracy of 15 to 100 metres. Inertial navigation complements GPS in that it provides relative positioning and is totally self-contained. These two positioning sensors are ideally suited for system integration for although there is not necessarily an improvement in accuracy, the integration of GPS with inertial navigation systems (INS) does enable an increase in system performance.

Sign in / Sign up

Export Citation Format

Share Document