The trajectory planning system for spraying robot based on k-means clustering and NURBS curve optimization

Author(s):  
Haichu Chen ◽  
Chenglong Guo ◽  
Zhifeng Wang ◽  
Tao Wen ◽  
Zhiming Zeng ◽  
...  
2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110027
Author(s):  
Jianqiang Wang ◽  
Yanmin Zhang ◽  
Xintong Liu

To realize efficient palletizing robot trajectory planning and ensure ultimate robot control system universality and extensibility, the B-spline trajectory planning algorithm is used to establish a palletizing robot control system and the system is tested and analyzed. Simultaneously, to improve trajectory planning speeds, R control trajectory planning is used. Through improved algorithm design, a trajectory interpolation algorithm is established. The robot control system is based on R-dominated multi-objective trajectory planning. System stack function testing and system accuracy testing are conducted in a production environment. During palletizing function testing, the system’s single-step code packet time is stable at approximately 5.8 s and the average evolutionary algebra for each layer ranges between 32.49 and 45.66, which can save trajectory planning time. During system accuracy testing, the palletizing robot system’s repeated positioning accuracy is tested. The repeated positioning accuracy error is currently 10−1 mm and is mainly caused by friction and the machining process. By studying the control system of a four-degrees-of-freedom (4-DOF) palletizing robot based on the trajectory planning algorithm, the design predictions and effects are realized, thus providing a reference for more efficient future palletizing robot design. Although the working process still has some shortcomings, the research has major practical significance.


2009 ◽  
Vol 32 (2) ◽  
pp. 215-228 ◽  
Author(s):  
Sheng‐Jung Tseng ◽  
Kuan‐Yuan Lin ◽  
Jiing‐Yih Lai ◽  
Wen‐Der Ueng

Robotica ◽  
2005 ◽  
Vol 23 (4) ◽  
pp. 467-477 ◽  
Author(s):  
Waldir L. Roque ◽  
Dionísio Doering

This paper discusses the techniques and their applications in the development of a path planning system composed of three modules, namely: global vision (GVM), trajectory planning (TPM) and navigation control (NCM). The GVM captures and processes the workspace image to identify the obstacle and the robot configurations. These configurations are used by the TPM to generate the Voronoi roadmap, to compute the maximal clearance shortest feasible path and the visibility pathway between two configurations. The NCM controls the robot functionalities and navigation. To validate the path planning system, three sets of experiments have been conducted using the Lab robot Khepera, which have shown very good results.


Author(s):  
Chunyu Zhang ◽  
Liwei Wang ◽  
Xinghu Yu ◽  
Mingsi Tong ◽  
Weiyang Lin ◽  
...  

2009 ◽  
Vol 16-19 ◽  
pp. 925-929
Author(s):  
Yu Liu ◽  
Jie Liu

Focusing on the problem of NURBS curve interpolation in high speed manufacture, a new trajectory planning algorithm, which is suitable for chord error closed loop controlled interpolator is proposed. This tragjectory can determine accelerating, decelerating or maintenance last velocity in the next period via judging the braking distance. By the way of testing different calculating time under different CPU core, the real-time characteristic is validated. The simulation shows that chord error closed loop interpolator can automatically adjust the velocity to satisfying the precision demand, through calculating the curvature. In addition, it can assure that the maximal velocity and the acceleration were equal to the referenced parameters and machine runs with the dynamic characteristic of operator set completely.


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