1.School of Mechanical and Electrical Engineering, Southwest Petroleum University, Chengdu 610500, China 2.School of Intelligent Manufacturing, Chengdu Technology University, Chengdu 611730, China 3.Sichuan Special Equipment Inspection Institute, Chengdu 610061, China
Aiming at the difficulty of wall-climbing robot in wall sensing and automated detection of large petrochemical equipment, an improved RTAB-Map (real-time appearance-based mapping) algorithm was proposed to realize the wall-climbing robot's localization, mapping and navigation by fusing multiple sensor data. Firstly, a robot motion chassis with wall adsorption ability was built to ensure the flexible and stable movement of the wall-climbing robot on the wall surface. Secondly, to address the cumulative error of the odometer resulting from the wall-climbing robot's slippage on the wall surface, the extended Kalman filter was utilized to fuse the data of encoder and inertial measurement unit to provide accurate odometer information for mapping and navigation. Thirdly, based on the RTAB-Map algorithm, the data of depth camera, LiDAR and odometer were fused to generate 2D grid and 3D point cloud map to realize a complete description of the equipment wall, and the navigation algorithm framework of the wall-climbing robot was constructed based on the fusion data. Finally, the experimental validation was carried out on the equipment wall. The results showed that the yaw angle error could be significantly reduced by using fusion mileage method, the average error of yaw angle was reduced by 88.94% compared with that under wheel odometer planning with an average error of 0.78°. The improved RTAB-Map algorithm improved the wall-climbing robot's mapping and sensing ability in the wall environment, and realized the autonomous navigation combined with the path planning algorithm. The research results have a certain reference significance for the research and application of automated detection technology of wall-climbing robots.
Chao QIN,Donglin TANG,Dongpan YOU,Chao DING,Sheng RAO,Yuanyuan HE. Research on navigation of wall-climbing robot based on improved RTAB-Map algorithm. Chinese Journal of Engineering Design, 2025, 32(1): 32-41.
Table 1Main technical parameters of chassis structure of wall-climbing robot
Fig.3 Improved RTAB-Map algorithm framework
Fig.4 Sensor data synchronization process
Fig.5 Navigation algorithm framework
Fig.6 A* algorithm schematic
Fig.7 Schematic diagram of robot wall trajectory reckoning
Fig.8 Odometer error test site
Fig.9 Movement trajectory of wall-climbing robot
Fig.10 Yaw angle of wall-climbing robot
Fig.11 Yaw angle error of wall-climbing robot
序号
融合前误差/(°)
融合后误差/(°)
最大值
平均值
最大值
平均值
1
13.27
6.38
2.12
0.85
2
12.75
6.03
1.80
0.68
3
13.99
8.60
0.48
0.02
4
12.75
6.06
3.37
0.60
5
13.60
7.64
3.57
1.82
6
13.07
7.00
2.18
0.56
7
13.63
6.98
2.06
0.51
8
14.42
8.79
2.55
0.53
9
13.19
6.40
3.35
1.38
10
13.92
6.43
2.02
0.85
Table 2Yaw angle errors of wall-climbing robot before and after fusion
Fig.12 Robot wall climbing experiment platform
Fig.13 Wall environment mapping effect
Fig.14 Robot navigation experiment on wall
参数
数值
参数
数值
最大牵引速度/(m/s)
0.15
最大角速度/(rad/s)
0.5
最小牵引速度/(m/s)
0
最小角速度/(rad/s)
0.1
最大加/减速度/（m/s2）
0.5
最大角加/减速度/（rad/s2）
3.5
牵引速度采样点数量/个
10
角速度采样点数量/个
10
Table 3Kinematic parameters for navigation experiment
Fig.15 Robot wall obstacle avoidance experiment
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