Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps

2014 ◽  
pp. 133-143 ◽  
Author(s):  
Sven Hellbach ◽  
Marian Himstedt ◽  
Frank Bahrmann ◽  
Martin Riedel ◽  
Thomas Villmann ◽  
...  
Keyword(s):  
Occupancy Grid ◽  
Semantic Labeling ◽  
Occupancy Grid Maps

scholarly journals Cloud Update of Tiled Evidential Occupancy Grid Maps for the Multi-Vehicle Mapping

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4119 ◽  
Author(s):  
Kichun Jo ◽  
Sungjin Cho ◽  
Chansoo Kim ◽  
Paulo Resende ◽  
Benazouz Bradai ◽  
...  
Keyword(s):  
Large Scale ◽  
Cloud Service ◽  
Mobile Internet ◽  
Intelligent Vehicles ◽  
Motion Sensors ◽  
Efficient Operation ◽  
Occupancy Grid ◽  
Occupancy Grid Maps ◽  
Sensor Information ◽  
Evidential Theory

Nowadays, many intelligent vehicles are equipped with various sensors to recognize their surrounding environment and to measure the motion or position of the vehicle. In addition, the number of intelligent vehicles equipped with a mobile Internet modem is increasing. Based on the sensors and Internet connection, the intelligent vehicles are able to share the sensor information with other vehicles via a cloud service. The sensor information sharing via the cloud service promises to improve the safe and efficient operation of the multiple intelligent vehicles. This paper presents a cloud update framework of occupancy grid maps for multiple intelligent vehicles in a large-scale environment. An evidential theory is applied to create the occupancy grid maps to address sensor disturbance such as measurement noise, occlusion and dynamic objects. Multiple vehicles equipped with LiDARs, motion sensors, and a low-cost GPS receiver create the evidential occupancy grid map (EOGM) for their passing trajectory based on GraphSLAM. A geodetic quad-tree tile system is applied to manage the EOGM, which provides a common tiling format to cover the large-scale environment. The created EOGM tiles are uploaded to EOGM cloud and merged with old EOGM tiles in the cloud using Dempster combination of evidential theory. Experiments were performed to evaluate the multiple EOGM mapping and the cloud update framework for large-scale road environment.

scholarly journals Hybrid Metric-Topological 3D Occupancy Grid Maps for Large-scale Mapping

2016 ◽  
Vol 49 (15) ◽  
pp. 230-235 ◽  
Author(s):  
Patrik Schmuck ◽  
Sebastian A. Scherer ◽  
Andreas Zell
Keyword(s):  
Large Scale ◽  
Occupancy Grid ◽  
Occupancy Grid Maps

scholarly journals Estimating Object Shape and Movement Using Local Occupancy Grid Maps

2019 ◽  
Vol 52 (8) ◽  
pp. 87-92 ◽  
Author(s):  
Jannik Quehl ◽  
Shengchao Yan ◽  
Sascha Wirges ◽  
Jan-Hendrik Pauls ◽  
Martin Lauer
Keyword(s):  
Object Shape ◽  
Occupancy Grid ◽  
Occupancy Grid Maps

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.

Construction of Minimized Topological Graphs on Occupancy Grid Maps Based on GVD and Sensor Coverage Information

2013 ◽  
Vol 75 (3-4) ◽  
pp. 457-474 ◽  
Author(s):  
E. G. Tsardoulias ◽  
A. T. Serafi ◽  
M. N. Panourgia ◽  
A. Papazoglou ◽  
L. Petrou
Keyword(s):  
Sensor Coverage ◽  
Topological Graphs ◽  
Occupancy Grid ◽  
Occupancy Grid Maps
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