An evaluation of 2D SLAM techniques available in Robot Operating System

@article{Santos2013AnEO,
  title={An evaluation of 2D SLAM techniques available in Robot Operating System},
  author={Jo{\~a}o Machado Santos and David Portugal and Rui P. Rocha},
  journal={2013 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)},
  year={2013},
  pages={1-6}
}
In this work, a study of several laser-based 2D Simultaneous Localization and Mapping (SLAM) techniques available in Robot Operating System (ROS) is conducted. [] Key Result Such analysis is fundamental to decide which solution to adopt according to the properties of the intended final application.
View on IEEE
eprints.lincoln.ac.uk
191 Citations
Highly Influential Citations
16
Background Citations
50
Methods Citations
78
Results Citations
7

Figures and Tables from this paper

191 Citations

Citation Type

Citation Type

An evaluation of Lidar-based 2D SLAM techniques with an exploration mode
TLDR
This paper presents a study of three most common laser-based 2D SLAM techniques: Gmapping, KartoSLAM and Cartographer, which was applied to construct maps combined with autonomous exploration.
Predicting Performance of SLAM Algorithms
TLDR
This paper presents a novel method that allows the ex ante prediction of the performance of a SLAM algorithm in an unseen environment, before it is actually run, on the basis of data collected in a number of simulated environments.
Comparison of Two SLAM Algorithms Provided by ROS (Robot Operating System)
TLDR
This paper aims to compare the result of the two SLAM algorithms (Hector SLAM, GMapping) in terms of map accuracy and the average time taken for the Waffle Pi (robot model) to reach its various destinations in an unknown indoor environment.
Performance comparison of 2D SLAM techniques available in ROS using a differential drive robot
TLDR
This document presents a performance comparison of three 2D SLAM techniques available in ROS: Gmapping, Hec-torSLAM and CRSM SLAM, using a Roomba 645 robotic platform with differential drive and a RGB-D Kinect sensor as an emulator of a scanner lasser.
Towards a Framework for SLAM Performance Investigation on Mobile Robots
  • Duc-Tuan Ngo, Hoang-Anh Pham
  • Computer Science
    2020 International Conference on Information and Communication Technology Convergence (ICTC)
  • 2020
TLDR
The proposed framework for studying SLAM performance in terms of accuracy, processing time, and hardware resource consumption is developed and shows that Hector SLAM has better accuracy performance than Cartographer.
Evaluation of SLAM Algorithms for Highly Dynamic Environments
TLDR
Four different 2D SLAM algorithms that are available in Robotic Operating System (ROS) are employed and evaluated through visual inspection of produced maps and the difference between the object positions in obtained maps and their real positions in the environment.
Experimental evaluation of ROS compatible SLAM algorithms for RGB-D sensors
TLDR
This work presents an experimental evaluation of five SLAM algorithms usable on RGB-D sensors, namely, Gmapping, Hector SLAM, ORBSLAM, OrB SLAM 2 and RTAB-Map, which should provide insight for roboticists seeking a SLAM solution for indoor applications.
A quantitative study of mapping and localization algorithms on ROS based differential robot
TLDR
A quantitative analysis of many algorithms developed to enhance the Simultaneous localization and Mapping process and their performance on various parameters on a differential robot equipped with 2D Laser scanner.
SLAMfusion: Fusing SLAM Methods for Improved Robustness
TLDR
A proposal to make a more robust SLAM by running three SLAM methods in parallel and using their information to produce a better estimate of the robot's surroundings, which shows smaller error than any of the three fused methods alone.
Autonomous 2D SLAM and 3D mapping of an environment using a single 2D LIDAR and ROS
TLDR
An algorithm that performs an autonomous 3D reconstruction of an environment with a single 2D Laser Imaging Detection and Ranging sensor as well as its implementation on a mobile platform using the Robot Operating System (ROS).
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 16 REFERENCES
Comparison of indoor robot localization techniques in the absence of GPS
TLDR
The performance of several implementations of the main class of localization algorithms that use a laser, Simultaneous Localization And Mapping (SLAM) on the RAWSEEDS benchmark is reported.
On measuring the accuracy of SLAM algorithms
TLDR
A framework for analyzing the results of a SLAM approach based on a metric for measuring the error of the corrected trajectory is proposed, which overcomes serious shortcomings of approaches using a global reference frame to compute the error.
A flexible and scalable SLAM system with full 3D motion estimation
TLDR
A system for fast online learning of occupancy grid maps requiring low computational resources is presented that combines a robust scan matching approach using a LIDAR system with a 3D attitude estimation system based on inertial sensing to achieve reliable localization and mapping capabilities in a variety of challenging environments.
tinySLAM: A SLAM algorithm in less than 200 lines C-language program
  • B. Steux, O. Hamzaoui
  • Computer Science
    2010 11th International Conference on Control Automation Robotics & Vision
  • 2010
TLDR
A Laser-SLAM algorithm which can be programmed in less than 200 lines C-language program and shows the possibility to perform complex tasks using simple and easily programmable algorithms.
Globally Consistent Range Scan Alignment for Environment Mapping
TLDR
The problem of consistent registration of multiple frames of measurements (range scans), together with therelated issues of representation and manipulation of spatialuncertainties are studied, to maintain all the local frames of data as well as the relative spatial relationships between localframes.
FastSLAM: a factored solution to the simultaneous localization and mapping problem
TLDR
This paper presents FastSLAM, an algorithm that recursively estimates the full posterior distribution over robot pose and landmark locations, yet scales logarithmically with the number of landmarks in the map.
Convergence and Consistency Analysis for Extended Kalman Filter Based SLAM
TLDR
It is shown that the robot orientation uncertainty at the instant when landmarks are first observed has a significant effect on the limit and/or the lower bound of the uncertainties of the landmark position estimates.
A Linear Approximation for Graph-Based Simultaneous Localization and Mapping
TLDR
This article investigates the problem of Simultaneous Localization and Mapping (SLAM) from the perspective of linear estimation theory, combining tools belonging to linear estimation and graph theory to propose a closed-form approximation to the full SLAM problem.
Efficient Sparse Pose Adjustment for 2D mapping
TLDR
This paper compares their method, called Sparse Pose Adjustment (SPA), with competing indirect methods, and shows that it outperforms them in terms of convergence speed and accuracy, and demonstrates its effectiveness on a large set of indoor real-world maps, and a very large simulated dataset.
G2o: A general framework for graph optimization
TLDR
G2o, an open-source C++ framework for optimizing graph-based nonlinear error functions, is presented and demonstrated that while being general g2o offers a performance comparable to implementations of state-of-the-art approaches for the specific problems.
...
1
2
...