An Improved Simultaneous Localization and Mapping System

Yunlei Sun; Qingxiao Wu

doi:10.3788/LOP56.161013

Laser & Optoelectronics Progress, Volume. 56, Issue 16, 161013(2019)

An Improved Simultaneous Localization and Mapping System

Yunlei Sun^{1,2,3,4,5、*} and Qingxiao Wu^1,2,4,5、**

Author Affiliations

¹ Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China

² Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China

³ University of Chinese Academy of Sciences, Beijing 100049, China

⁴ Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China

⁵ Liaoning Provincial Key Laboratory of Image Understanding and Computer Vision, Shenyang, Liaoning 110016, China

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Figures & Tables(9)

Fig. 1. Overview of improved system

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Fig. 2. Schematic of four-layer image pyramid model and improved camera pose estimation process

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Fig. 3. Unary edge and binary edge models in g2o library. (a) Unary edge model; (b) binary edge model

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Fig. 4. Comparison between ground truths and real trajectories of cameras generated by improved ORB-SLAM2 system on four frame sequences. (a) fr1/desk frame sequence; (b) fr1/desk2 frame sequence; (c) fr1/plant frame sequence; (d) fr1/xyz frame sequence

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Fig. 5. Reconstruction results and camera trajectories on four frame sequences by improved ORB-SLAM2 system on ICL-NUIM benchmark datasets. (a) lr_kt0; (b) lr_kt1; (c) lr_kt12; (d) lr_kt3

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Fig. 6. Comparison of reconstruction results of Kintinuous, ElasticFusion, and improved ORB-SLAM2 systems on closed-loop region of lr_kt3 frame sequence. (a) Kintinuous system; (b) ElasticFusion system; (c) improved ORB-SLAM2 system

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Table 1. Comparison of camera trajectories on TUM RGB-D benchmark datasets

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Table 1. Comparison of camera trajectories on TUM RGB-D benchmark datasets

Sequence	Relative path /m
Sequence	DVO SLAM	Kintinuous	ElasticFusion	ORB-SLAM2	Improved system
fr1/desk	0.022	0.142	0.022	0.016	0.016
fr1/plant	0.027	0.059	0.043	0.016	0.014
fr1/teddy	0.049	0.237	0.091	0.035	0.056
fr1/room	0.064	0.182	0.198	0.059	0.056
fr1/360	0.074	0.202	0.270	failed	0.129
fr1/desk2	0.035	0.140	0.058	0.031	0.025
fr1/floor	0.035	0.140	0.058	0.031	0.035
fr1/rpy	0.022	0.041	0.037	0.064	0.023
fr1/xyz	0.013	0.021	0.014	0.009	0.009

Table 2. Details of four frame sequences on ICL-NUIM benchmark datasets
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Table 2. Details of four frame sequences on ICL-NUIM benchmark datasets
Sequence Frame Length /m Withloop
lr_kt0 1510 6.54 No
lr_kt1 967 2.05 No
lr_kt2 882 8.43 No
lr_kt3 1242 11.32 Yes

Table 3. Comparison of 3D models on ICL-NUIM benchmark datasets
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Table 3. Comparison of 3D models on ICL-NUIM benchmark datasets
System 3D model result /m
lr_kt0 lr_kt1 lr_kt2 lr_kt3
Kintinuous 0.087 0.470 0.162 0.205
ElasticFusion 0.058 0.505 0.185 0.219
ImprovedORB-SLAM2 0.007 0.467 0.155 0.190