A novel positioning method of anti-punching drilling robot based on the fusion of multi-IMUs and visual image

Si, Lina; Wang, Zhongbin; Li, Jiahao; Wei, Dong; Zhao, Siming

doi:10.1016/j.isatra.2023.01.010

Cited by 7 publications

(5 citation statements)

References 18 publications

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“…The IMU measures the acceleration of the robot’s motion via an accelerometer and measures the angular velocity of motion via a gyroscope, calculating the current attitude through an attitude fusion algorithm ( Pu et al., 2023 ). Si et al. (2023) aimed at the issues of significant positioning and mapping errors caused by LiDAR point cloud distortion, designed a point cloud distortion correction method based on continuous-time trajectories of IMUs, established a data fusion model between LiDAR and IMUs, and proposed a positioning and mapping method for anti-collision drilling robots based on tightly coupled IMU-LiDAR, effectively improving the precision and performance of positioning and map building.…”

Section: Related Workmentioning

confidence: 99%

Research on autonomous navigation system of greenhouse electric crawler tractor based on LiDAR

Guo,

Li,

Wang

et al. 2024

Front. Plant Sci.

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The application of autonomous navigation technology of electric crawler tractors is an important link in the development of intelligent greenhouses. Aiming at the characteristics of enclosed and narrow space and uneven ground potholes in greenhouse planting, to improve the intelligence level of greenhouse electric crawler tractors, this paper develops a navigation system of electric crawler tractors for the greenhouse planting environment based on LiDAR technology. The navigation hardware system consists of five modules: the information perception module, the control module, the communication module, the motion module, and the power module. The software system is composed of three layers: the application layer, the data processing layer, and the execution layer. The developed navigation system uses LiDAR, Inertial Measurement Unit (IMU) and wheel speed sensor to sense the greenhouse environment and the crawler tractor’s information, employs the Gmapping algorithm to build the greenhouse environment map, and utilizes the adaptive Monte Carlo positioning algorithm for positioning. The simulation test of different global path planning algorithms in Matlab shows that the A* algorithm obtains the optimal overall global path. In the scene of map 5, the path planned by the A* algorithm is the most significant, and the number of inflection points is reduced by 40.00% and 87.50%, respectively; meanwhile, the path length is the same as that of the Dijkstra algorithm, but the runtime is reduced by 68.87% and 81.49%, respectively; compared with the RRT algorithm, the path length is reduced by 7.27%. Therefore, the A* algorithm and the Dynamic Window Approach (DWA) method are used for tractor navigation and obstacle avoidance, which ensures global path optimality while also achieving effective local path planning for obstacle avoidance. The test results suggest that the maximum lateral deviation of the built map is 6 cm, and the maximum longitudinal deviation is 16 cm, which meets the requirement of map accuracy. Additionally, the results of the navigation accuracy test indicate that the maximum lateral deviation of navigation is less than 13 cm, the average lateral deviation is less than 7 cm, and the standard lateral deviation is less than 8 cm. The maximum heading deviation is less than 14°, the average heading deviation is less than 7°, and the standard deviation is less than 8°. These results show that the developed navigation system meets the navigation accuracy requirements of electric crawler tractors in the greenhouse environment.

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Section: Related Workmentioning

confidence: 99%

Research on autonomous navigation system of greenhouse electric crawler tractor based on LiDAR

Guo,

Li,

Wang

et al. 2024

Front. Plant Sci.

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“…The positive value is the upper deviation, and the negative value is the lower deviation. Its calculation equation is shown in Equation (3). The difference between the up and down displacement of the actual horizontal drilling track and the ideal horizontal drilling track (horizontal line) is called the left and right deviation.…”

Section: Up and Down Displacementmentioning

confidence: 99%

“…The anti-scour drilling robot is the key equipment for drilling pressure relief, and its intelligence level is the necessary condition for realizing unmanned operations. In the process of horizontal drilling of drill pipe, once the drilling track deviates, the sticking will be caused, then the drilling could not reach the expected depth with the poor effect of the pressure relief [3]. At the same time, the problem of drilling deviation will also pose a threat to the safety of the roof and floor, which will directly affect the safety and construction efficiency of the drilling pressure relief process.…”

Section: Introductionmentioning

confidence: 99%

Prediction Model of Horizontal Drilling Trajectory of Anti-collision Drilling Robot

Kang

Hua

2023

J. Phys.: Conf. Ser.

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The horizontal drilling trajectory of the anti-collision drilling robot is taken as the research object and its drilling trajectory prediction model is established in this paper. The drilling trajectory is affected by many factors, such as the structural parameters of the auger, the drill bit, the drilling process parameters, and the geological characteristics of the coal seam, etc., which results in the existence of multi-level time-scale structure and localization characteristics of the drilling trajectory data in the time domain. The wavelet analysis method can decompose the relatively complex non-stationary time series problem into low-frequency decomposition signals representing trend items and high-frequency decomposition signals representing periodicity and randomness. It can not only predict the main trend of drilling trajectory changes but also effectively predict sudden load changes and short-term changes. Based on this, a new prediction method is proposed in this paper. Firstly, the data is decomposed into relatively simple component signals using wavelet decomposition technology, then the prediction models are established according to the characteristics of each component signal. Finally, the drilling trajectory prediction model is established by synthesizing the prediction results. The anti-impact drilling robot drilling test bed is set up and the drilling experiments are carried out to verify the effectiveness of the model, which can lay the foundation for the anti-impact drilling robot drilling deflection control.

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“…The efficiency and reliable operation of the lifting hydraulic cylinders directly affect the lifting position and pitch angle of the DTAAS. However, the position-tracking accuracy and stability of the DTAAS are decreased because of the model uncertainties and external disturbances [ 5 , 6 ]. Considering the different position-tracking conditions, the control methods of the DTAAS are still in exploration.…”

Section: Introductionmentioning

confidence: 99%

Observer-Based Adaptive Sliding Mode Compensation Position-Tracking Control for Drilling Tool Attitude Adjustment

Gu,

Wang,

Yan

et al. 2024

Sensors

Self Cite

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This study develops an adaptive sliding mode control approach for a drilling tool attitude adjustment system, aiming at solving the problems of model uncertainties and insufficient ability of disturbance suppression during the regulation behavior. To further improve the performance of the position-tracking loop in terms of response time, tracking accuracy, and robustness, a state observer based on an improved radial basis function is designed to approximate the model uncertainties, a valve dead-zone compensate controller is used to reduce control deviation, an adaptive sliding mode controller is designed to improve the position-tracking precision and attenuate sliding mode chattering. Finally, simulation and experimental results are carried out to verify the observability of the model uncertainties and position-tracking errors of the drilling tool attitude adjustment system, which can effectively improve the position-tracking performance and robustness of the drilling tool attitude adjustment system.

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A novel positioning method of anti-punching drilling robot based on the fusion of multi-IMUs and visual image

Cited by 7 publications

References 18 publications

Research on autonomous navigation system of greenhouse electric crawler tractor based on LiDAR

Research on autonomous navigation system of greenhouse electric crawler tractor based on LiDAR

Prediction Model of Horizontal Drilling Trajectory of Anti-collision Drilling Robot

Observer-Based Adaptive Sliding Mode Compensation Position-Tracking Control for Drilling Tool Attitude Adjustment

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