scholarly journals A novel map-merging technique for occupancy grid-based maps using multiple robots: a semantic approach

2019 ◽  
Vol 27 (5) ◽  
pp. 3980-3993 ◽  
Author(s):  
Akif DURDU ◽  
Mehmet KORKMAZ
Keyword(s):  
Multiple Robots ◽  
Semantic Approach ◽  
Occupancy Grid ◽  
Grid Based ◽  
Map Merging

scholarly journals A Review on Map-Merging Methods for Typical Map Types in Multiple-Ground-Robot SLAM Solutions

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6988
Author(s):  
Shuien Yu ◽  
Chunyun Fu ◽  
Amirali K. Gostar ◽  
Minghui Hu
Keyword(s):  
Multiple Robots ◽  
Working Mechanism ◽  
Topological Maps ◽  
Occupancy Grid ◽  
Localization And Mapping ◽  
Robot Systems ◽  
Feature Based ◽  
Occupancy Grid Maps ◽  
Multi Robot ◽  
Map Merging

When multiple robots are involved in the process of simultaneous localization and mapping (SLAM), a global map should be constructed by merging the local maps built by individual robots, so as to provide a better representation of the environment. Hence, the map-merging methods play a crucial rule in multi-robot systems and determine the performance of multi-robot SLAM. This paper looks into the key problem of map merging for multiple-ground-robot SLAM and reviews the typical map-merging methods for several important types of maps in SLAM applications: occupancy grid maps, feature-based maps, and topological maps. These map-merging approaches are classified based on their working mechanism or the type of features they deal with. The concepts and characteristics of these map-merging methods are elaborated in this review. The contents summarized in this paper provide insights and guidance for future multiple-ground-robot SLAM solutions.

Dynamic world modeling for a mobile robot among moving objects

Robotica ◽  
1996 ◽  
Vol 14 (5) ◽  
pp. 553-560
Author(s):  
Yuefeng Zhang ◽  
Robert E. Webber
Keyword(s):  
Mobile Robot ◽  
Hough Transform ◽  
Moving Objects ◽  
Grid Method ◽  
Experimental Results ◽  
Sensor Data ◽  
Probabilistic Estimation ◽  
Occupancy Grid ◽  
World Modeling ◽  
Grid Based

SUMMARYA grid-based method for detecting moving objects is presented. This method involves the extension and combination of two methods: (1) the Hough Transform and (2) the Occupancy Grid method. The Occupancy Grid method forms the basis for a probabilistic estimation of the location and velocity of objects in the scene from the sensor data. The Hough Transform enables the new method to handle non-integer velocity values. A model for simulating a sonar ring is also presented. Experimental results show that this method can handle objects moving at non-integer velocities.

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

A Probability Occupancy Grid Based Approach for Real-Time LiDAR Ground Segmentation

2020 ◽  
Vol 21 (3) ◽  
pp. 998-1010 ◽  
Author(s):  
Zhongzhen Luo ◽  
Martin V. Mohrenschildt ◽  
Saeid Habibi
Keyword(s):  
Real Time ◽  
Occupancy Grid ◽  
Ground Segmentation ◽  
Grid Based

scholarly journals The Characteristics of the Map Merging Methods: A Survey

2010 ◽  
Vol 41 (1) ◽  
pp. 113-121 ◽  
Author(s):  
Ilze Andersone
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
Research Field ◽  
Autonomous Mobile Robots ◽  
Multiple Robots ◽  
Characteristic Set ◽  
Robotic Mapping ◽  
New Research ◽  
Multi Robot ◽  
Map Merging

The Characteristics of the Map Merging Methods: A SurveyThe development of the autonomous mobile robots is a popular field of research in the artificial intelligence for more than twenty years. An important prerequisite for creation of autonomous robot is the ability to create a map of the environment. However there are several problems in the robotic mapping that are still not completely solved. The use of multiple robots for mapping solves some of these problems, but in this case several new problems, specific to multi-robot mapping, arise. One of the problems in multi-robot mapping is merging all of the local maps that robots have created into one global map. The application of the robot teams in the exploration is a relatively new research field and initially methods for multi-robot mapping were just extended single robot mapping methods. Consequently the map merging problem was simplified. The research of map merging has only recently evolved, thus existing papers on the map merging describe specific map merging methods and there are no comprehensive surveys on the state of the art in the field of map merging. Therefore the goal of this paper is to describe the situation in the field of the map merging and to identify the main characteristics of the map merging methods. The interrelations of these characteristics can then be identified and the corresponding map merging approaches of each characteristic set named.

scholarly journals The influence of the map merging order on the resulting global map in multi-robot mapping

2012 ◽  
Vol 13 (1) ◽  
pp. 22-28
Author(s):  
Ilze Andersone
Keyword(s):  
Autonomous Robot ◽  
Multiple Robots ◽  
Important Prerequisite ◽  
Robot Teams ◽  
Mapping Process ◽  
As If ◽  
Multi Robot ◽  
Map Merging

An important prerequisite for creation of an autonomous robot is the ability to create the map of the environment. While the use of robot teams becomes more and more widely used, the issue of robot coordination becomes one of the central questions to be addressed. If multiple robots are used for the exploration of the environment, their collected information has to be fused into one general global map. This problem is called map merging. In the case, when more than two robots map the environment, it is possible that the order of map merging can influence the quality of the result - the global map. However, most researches in the map merging field address the problem as if the recommended order of map merging were known. The goal of this paper is to prove that the merging order can greatly influence the resulting global map and discuss the consequences this knowledge makes in the mapping process.

Sign in / Sign up

Export Citation Format

Share Document