Lidar SLAM Algorithm Based on Online Point Cloud Removal in Pseudo Occupied Area

Qingxuan Zeng; Qiang Li; Weizhi Nie

doi:10.3788/AOS230839

Journals >Acta Optica Sinica >Volume 43 >Issue 20 >Page 2028001 > Article

Acta Optica Sinica
Vol. 43, Issue 20, 2028001 (2023)

Lidar SLAM Algorithm Based on Online Point Cloud Removal in Pseudo Occupied Area

Qingxuan Zeng¹, Qiang Li^1,*, and Weizhi Nie²

Author Affiliations

¹School of Microelectronics, Tianjin University, Tianjin 300072, China

²School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China

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DOI: 10.3788/AOS230839 Cite this Article Set citation alerts

Qingxuan Zeng, Qiang Li, Weizhi Nie. Lidar SLAM Algorithm Based on Online Point Cloud Removal in Pseudo Occupied Area[J]. Acta Optica Sinica, 2023, 43(20): 2028001 Copy Citation Text

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Fig. 1. Overall framework of DOR-LOAM system

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Fig. 2. Schematic of pseudo occupancy region division

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Fig. 3. Schematic of dynamic point cloud memory area formed by point cloud matching. (a) A priori map; (b) current frame

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Fig. 4. Schematic of sliding window mode of a priori map

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Fig. 5. Sequence 00 and sequence 07 dynamic point cloud removal effect for different algorithms. (a) Original iamges; (b) Removert algorithm; (c) ERASOR algorithm; (d) DOR-LOAM algorithm

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Fig. 6. Detail of point cloud removal effect of sequence 05 for different algorithms. (a) Ground truth; (b) ERASOR algorithm; (c) DOR-LOAM algorithm

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Fig. 7. Comparison of tracks from sequence 00 to sequence 09

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Fig. 8. Comparison of dynamic removal rate parameters

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Fig. 9. Comparison of running time of each module

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Sequence	Evaluation index	Removert	ERASOR	DOR-LOAM
00	$R_{P}$	85.50	93.98	97.29
	$R_{R}$	99.35	97.08	97.06
	$F_{1}$	91.90	95.50	97.18
01	$R_{P}$	94.22	91.49	96.45
	$R_{R}$	93.61	95.38	94.87
	$F_{1}$	93.91	93.40	95.65
02	$R_{P}$	76.32	87.73	84.27
	$R_{R}$	96.80	97.01	97.30
	$F_{1}$	85.35	92.10	90.32
05	$R_{P}$	86.90	88.73	95.33
	$R_{R}$	87.88	98.26	97.53
	$F_{1}$	87.39	93.30	96.42
07	$R_{P}$	80.69	90.62	97.30
	$R_{R}$	98.82	99.27	98.80
	$F_{1}$	88.84	94.80	98.04
Average	$R_{P}$	84.726	90.51	94.13
	$R_{R}$	95.292	97.40	97.11
	$F_{1}$	89.478	93.82	95.52

Table 1. Comparison of dynamic point cloud removal accuracy for different algorithms

Sequence	E-LOAM		T-LOAM		NDT-LOAM	PSF-LO	SuMa++		DOR-LOAM
	${\bar{E}}_{t r a n s}$ /%	${\bar{E}}_{r o t}$ / ［（°）·m^-1］	${\bar{E}}_{t r a n s}$ /%	${\bar{E}}_{r o t}$ / ［（°）·m^-1］	${\bar{E}}_{t r a n s}$ /%	${\bar{E}}_{t r a n s}$ /%	${\bar{E}}_{t r a n s}$ /%	${\bar{E}}_{r o t}$ / ［（°）·m^-1］	${\bar{E}}_{t r a n s}$ /%	${\bar{E}}_{r o t}$ / ［（°）·m^-1］
00	1.17	0.0047	0.98	0.0060	0.79	0.64	0.64	0.0022	0.82	0.0028
01	2.92	0.0062	2.09	0.0052	1.46	1.32	1.60	0.0046	1.83	0.0050
02	2.36	0.0082	1.01	0.0039	1.09	0.87	1.00	0.0037	1.11	0.0036
03	1.16	0.0068	1.10	0.0082	0.65	0.75	0.67	0.0046	0.65	0.0043
04	1.39	0.0050	0.68	0.0068	0.31	0.66	0.37	0.0026	0.59	0.0038
05	0.82	0.0036	0.55	0.0032	0.54	0.45	0.40	0.0020	0.54	0.0023
06	1.34	0.0057	0.56	0.0031	0.56	0.47	0.46	0.0021	0.48	0.0023
07	1.21	0.0066	0.50	0.0047	0.27	0.46	0.34	0.0019	0.37	0.0025
08	1.63	0.0063	0.94	0.0033	1.04	0.94	1.10	0.0035	0.93	0.0030
09	1.36	0.0057	0.80	0.0040	0.74	0.56	0.47	0.0023	0.71	0.0028
10	1.84	0.0063	1.12	0.0061	1.12	0.54	0.66	0.0028	0.92	0.0037
Average	1.56	0.0059	0.93	0.0049	0.90	0.74	0.70	0.0029	0.81	0.0033

Table 2. Accuracy comparison of different algorithms

Algorithm

Baseline

Baseline+DOR

E-LOAM

T-LOAM

NDT-LOAM

{\bar{E}}_{t r a n s}

1.28

0.81

1.56

0.93

0.90

${\bar{E}}_{r o t}$ /

［（°）·m^-1］

0.0044

0.0033

0.0059

0.0049

Average time /ms

76.33

87.48

77.38

100

Table 3. Comparison of ablation experiments and different algorithms

Qingxuan Zeng, Qiang Li, Weizhi Nie. Lidar SLAM Algorithm Based on Online Point Cloud Removal in Pseudo Occupied Area[J]. Acta Optica Sinica, 2023, 43(20): 2028001

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