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Indoor Robot SLAM with Multi-Sensor Fusion Cover

Figures & Tables

Figure 1.

Simulation fusion calculation diagram

Figure 2.

Extended Kalman filter fusion results

Figure 3.

Integrating odometer data

Figure 4.

Experimental scenario

Figure 5.

Laser and visual scanning range

Figure 6.

Robot model

Figure 7.

Simulation experimental environment

Figure 8.

Comparison of simulation experiments

Figure 9.

Real experimental environment

Figure 10.

Installation height of LiDAR

Figure 11.

Robot departure position

Figure 12.

Real environment mapping results

Experimental Result

Starting pointTarget pointWheel odometryErrorFusion odometryError
(0,0)(1.3,0)(1.347,0.035)(0.047,0.035)(1.324,0.029)(0.024, 0.029)
(1.3,-3.25)(1.391,-3.373)(0.091,0.123)(1.386,-3.322)(0.086, 0.072)
(0,-3.25)(0.152,-3.387)(0.152,0.137)(0.085,-3.316)(0.085, 0.066)
Mean error (0.097,0.098) (0.065, 0.056)

Local map fusion rules

2D excitation Optical radarDepth camera
OccupyemptyUncertain
OccupiedOccupyOccupyOccupy
emptyOccupyemptyempty
UncertainOccupyemptyUncertain

Positioning results

Actual location (m)Actual pose (°)GmappingVision + Laser
Estimated position (m)Estimated pose (°)Root mean square error of position (cm)Attitude error (°)Estimated position (m)Estimated pose (°)Root Mean square error of position (cm)Pose Error (°)
(6,0)30(6.085, 0.079)33.14911.6043.149(6.059, 0.037)31.0925.91.092
(6,-3)90(6.094,-3.081)94.63412.4084.634(6.064,-3.051)92.0438.1842.043
(6,-6)90(6.103,-6.089)95.00513.6125.005(6.072,-6.063)92.7299.5672.729
(0,-6)180(0.135,-6.112)186.02417.5416.024(0.089,-6.075)184.00711.6394.007
(0,0)0(0.156, 0.127)7.67820.1167.678(0.091, 0.08)4.9612.1174.96
Language: English
Page range: 10 - 21
Published on: Mar 28, 2024
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2024 Jionglin He, Jiaxiang Fang, Shuping Xu, Dingzhe Yang, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.