Fast SLAM using polar scan matching and particle weight based occupancy grid map for mobile robot

2011 ◽  
Author(s):  
Hyun Chul Roh ◽  
Chang Hun Sung ◽  
Min Tae Kang ◽  
Myung Jin Chung
Keyword(s):  
Mobile Robot ◽  
Scan Matching ◽  
Occupancy Grid ◽  
Grid Map ◽  
Occupancy Grid Map ◽  
Particle Weight

Development of Method Using a Combination of DGPS and Scan Matching for the Making of Occupancy Grid Maps for Localization

2013 ◽  
Vol 25 (3) ◽  
pp. 506-514 ◽  
Author(s):  
Junji Eguchi ◽  
◽  
Koichi Ozaki
Keyword(s):  
Autonomous Navigation ◽  
Laser Scanner ◽  
Tall Buildings ◽  
Filter Method ◽  
Scan Matching ◽  
Structure Information ◽  
Occupancy Grid ◽  
Grid Map ◽  
Accurate Localization ◽  
Occupancy Grid Map

This paper describes a method of making an occupancy grid map through the combined use of DGPS and scan matching. In outdoor environments such as city areas, high-accuracy localization is required for autonomous navigation. Scan matching with a laser scanner and an occupancy grid map consisting of precise structure information on the environment is one of the most accurate localization methods. However, mismatching on the map sometimes occurs, resulting in the robot losing its own position. Although a GPS device, an absolute positioning device, is valid for estimating position and attitude to a certain degree of accuracy, GPS often obtains erroneous positions for multipath problems which occur around tall buildings. In order to estimate the position and attitude of robots more stably, the authors have developed a method of making an occupancy grid map, which corresponds to DGPS directions and has an accurate shape, by using of some accurate DGPS measurement points and the SLAM method. In autonomous navigation, the robot trajectory is estimated using the particle filter method, evaluation and resampling are done using the two ways mentioned above, and attitude is calculated using DGPS measurement points and the result of scan matching. In this paper, the performance of the map-making method and localization method for autonomous navigation is shown through experiments which are evaluated as to the accuracy of the map in an actual environment.

Development of Autonomous Mobile Robot “MML-05” Based on i-Cart Mini for Tsukuba Challenge 2015

2016 ◽  
Vol 28 (4) ◽  
pp. 461-469 ◽  
Author(s):  
Tomoyoshi Eda ◽  
◽  
Tadahiro Hasegawa ◽  
Shingo Nakamura ◽  
Shin’ichi Yuta
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
The Self ◽  
Autonomous Mobile Robots ◽  
Autonomous Mobile Robot ◽  
Localization Method ◽  
Occupancy Grid ◽  
Grid Map ◽  
Local Grid ◽  
Occupancy Grid Map

[abstFig src='/00280004/04.jpg' width='300' text='Autonomous mobile robots entered in the Tsukuba Challenge 2015' ] This paper describes a self-localization method for autonomous mobile robots entered in the Tsukuba Challenge 2015. One of the important issues in autonomous mobile robots is accurately estimating self-localization. An occupancy grid map, created manually before self-localization has typically been utilized to estimate the self-localization of autonomous mobile robots. However, it is difficult to create an accurate map of complex courses. We created an occupancy grid map combining local grid maps built using a leaser range finder (LRF) and wheel odometry. In addition, the self-localization of a mobile robot was calculated by integrating self-localization estimated by a map and matching it to wheel odometry information. The experimental results in the final run of the Tsukuba Challenge 2015 showed that the mobile robot traveled autonomously until the 600 m point of the course, where the occupancy grid map ended.

Removal of sonar wave interference in multi-robot system for the efficient SLAM by randomized triggering time technique

2020 ◽  
Vol 17 (4) ◽  
pp. 535-542
Author(s):  
Ravinder Singh ◽  
Akshay Katyal ◽  
Mukesh Kumar ◽  
Kirti Singh ◽  
Deepak Bhola
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Cross Talk ◽  
Autonomous Navigation ◽  
Content Type ◽  
Occupancy Grid ◽  
Grid Map ◽  
Wave Interference ◽  
Sonar Sensor ◽  
Occupancy Grid Map

Purpose Sonar sensor-based mobile robot mapping is an efficient and low cost technique for the application such as localization, autonomous navigation, SLAM and path planning. In multi-robots system, numbers of sonar sensors are used and the sound waves from sonar are interacting with the sound wave of other sonar causes wave interference. Because of wave interference, the generated sonar grid maps get distorted which resulted in decreasing the reliability of mobile robot’s navigation in the generated grid maps. This research study focus in removing the effect of wave interfaces in the sonar mapping to achieve robust navigation of mobile robot. Design/methodology/approach The wrong perception (occupancy grid map) of the environment due to cross talk/wave interference is eliminated by randomized the triggering time of sonar by varying the delay/sleep time of each sonar sensor. A software-based approach randomized triggering technique (RTT) is design in laboratory virtual instrument engineering workbench (LabVIEW) that randomized the triggering time of the sonar sensor to eliminate the effect of wave interference/cross talk when multiple sonar are placed in face-forward directions. Findings To check the reliability of the RTT technique, various real-world experiments are perform and it is experimentally obtained that 64.8% improvement in terms of probabilities in the generated occupancy grid map has been attained when compared with the conventional approaches. Originality/value This proposed RTT technique maybe implementing for SLAM, reliable autonomous navigation, optimal path planning, efficient robotics vision, consistent multi-robotic system, etc.

scholarly journals Multivehicle Cooperative Local Mapping: A Methodology Based on Occupancy Grid Map Merging

2014 ◽  
Vol 15 (5) ◽  
pp. 2089-2100 ◽  
Author(s):  
Hao Li ◽  
Manabu Tsukada ◽  
Fawzi Nashashibi ◽  
Michel Parent
Keyword(s):  
Occupancy Grid ◽  
Grid Map ◽  
Occupancy Grid Map ◽  
Map Merging
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