scholarly journals Optimal Robot Control Using Modelica and Optimica

Author(s):  
Martin Hast ◽  
Johan Åkesson ◽  
Anders Robertsson
Keyword(s):  
IEE Review ◽  
1988 ◽  
Vol 34 (7) ◽  
pp. 280
Author(s):  
A.G. Blay
Keyword(s):  

Author(s):  
Seung-Jun Lee ◽  
Woojin Kim ◽  
Yang Koo Lee ◽  
DaeSub Yoon ◽  
Jun wook Lee
Keyword(s):  

1988 ◽  
Vol 21 (9) ◽  
pp. 266-271 ◽  
Author(s):  
G R Ward

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.


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