scholarly journals E-SLAM solution to the grid-based Localization and Mapping problem

2007 ◽  
Author(s):  
Luis Moreno ◽  
M. Luisa Munoz ◽  
Santiago Garrido ◽  
Fernando Martin
Keyword(s):  
Mapping Problem ◽  
Localization And Mapping ◽  
Grid Based

scholarly journals An Orthogonal Weighted Occupancy Likelihood Map with IMU-Aided Laser Scan Matching for 2D Indoor Mapping

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1742 ◽  
Author(s):  
Chuang Qian ◽  
Hongjuan Zhang ◽  
Jian Tang ◽  
Bijun Li ◽  
Hui Liu
Keyword(s):  
Laser Scanner ◽  
Location Based Services ◽  
Experimental Result ◽  
Measurement Unit ◽  
Indoor Environments ◽  
Localization And Mapping ◽  
Map Generation ◽  
Representation Method ◽  
Rigid Body Transformation ◽  
Grid Based

An indoor map is a piece of infrastructure associated with location-based services. Simultaneous Localization and Mapping (SLAM)-based mobile mapping is an efficient method to construct an indoor map. This paper proposes an SLAM algorithm based on a laser scanner and an Inertial Measurement Unit (IMU) for 2D indoor mapping. A grid-based occupancy likelihood map is chosen as the map representation method and is built from all previous scans. Scan-to-map matching is utilized to find the optimal rigid-body transformation in order to avoid the accumulation of matching errors. Map generation and update are probabilistically motivated. According to the assumption that the orthogonal is the main feature of indoor environments, we propose a lightweight segment extraction method, based on the orthogonal blurred segments (OBS) method. Instead of calculating the parameters of segments, we give the scan points contained in blurred segments a greater weight during the construction of the grid-based occupancy likelihood map, which we call the orthogonal feature weighted occupancy likelihood map (OWOLM). The OWOLM enhances the occupancy likelihood map by fusing the orthogonal features. It can filter out noise scan points, produced by objects, such as glass cabinets and bookcases. Experiments were carried out in a library, which is a representative indoor environment, consisting of orthogonal features. The experimental result proves that, compared with the general occupancy likelihood map, the OWOLM can effectively reduce accumulated errors and construct a clearer indoor map.

Data Association Analysis in Simultaneous Localization and Mapping Problem

2019 ◽  
Vol 11 (4) ◽  
Author(s):  
Hamzah Ahmad ◽  
◽  
Nur Aqilah Othman ◽  
Mohd Mawardi Saari ◽  
Mohd Syakirin Ramli ◽  
...  
Keyword(s):  
Association Analysis ◽  
Data Association ◽  
Simultaneous Localization And Mapping ◽  
Mapping Problem ◽  
Localization And Mapping

Grid-Based Scan-to-Map Matching for Accurate Simultaneous Localization and Mapping: Theory and Preliminary Numerical Study

2013 ◽  
Author(s):  
Kunjin Ryu ◽  
Tomonari Furukawa ◽  
Stanislaw Antol ◽  
Gamini Dissanayake
Keyword(s):  
Numerical Study ◽  
Estimation Error ◽  
Simultaneous Localization And Mapping ◽  
Map Matching ◽  
Normal Distributions ◽  
Localization And Mapping ◽  
Matching Technique ◽  
Global Matching ◽  
Mapping Theory ◽  
Grid Based

This paper presents a grid-based scan-to-map matching technique for accurate simultaneous localization and mapping (SLAM). At every acquisition of a new scan, the proposed technique estimates the relative position from which the previous scan was taken, and further corrects its estimation error by matching the new scan to the globally defined map. In order to achieve best scan-to-map matching at each acquisition, the map to match is represented as a grid map with multiple normal distributions (NDs) in each cell. Additionally, the new scan is also represented by NDs, developing a novel ND-to-ND matching technique. The ND-to-ND matching technique has significant potential in the enhancement of the global matching as well as the computational efficiency. Experimental results first show that the proposed technique successfully matches new scans to the map generating very small position and orientation errors, and then demonstrates the effectiveness of the multi-ND representation in comparison to the single-ND representation.

A Robust Solution to the Stereo-Vision-Based Simultaneous Localization and Mapping Problem with Steady and Moving Landmarks

2011 ◽  
Vol 25 (6-7) ◽  
pp. 765-788 ◽  
Author(s):  
Pubudu N. Pathirana ◽  
Andrey V. Savkinb ◽  
Samitha W. Ekanayake ◽  
Nicholas J. Bauer
Keyword(s):  
Stereo Vision ◽  
Simultaneous Localization And Mapping ◽  
Robust Solution ◽  
Mapping Problem ◽  
Localization And Mapping
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