Acceleration-level repetitive motion planning of redundant planar robots solved by a simplified LVI-based primal-dual neural network

2013 ◽  
Vol 29 (2) ◽  
pp. 328-343 ◽  
Author(s):  
Yunong Zhang ◽  
Huarong Wu ◽  
Zhijun Zhang ◽  
Lin Xiao ◽  
Dongsheng Guo
Keyword(s):  
Neural Network ◽  
Motion Planning ◽  
Repetitive Motion ◽  
Acceleration Level ◽  
Primal Dual ◽  
Planar Robots

Repetitive motion planning of PA10 robot arm subject to joint physical limits and using LVI-based primal–dual neural network

Mechatronics ◽  
2008 ◽  
Vol 18 (9) ◽  
pp. 475-485 ◽  
Author(s):  
Yunong Zhang ◽  
Xuanjiao Lv ◽  
Zhonghua Li ◽  
Zhi Yang ◽  
Ke Chen
Keyword(s):  
Neural Network ◽  
Motion Planning ◽  
Robot Arm ◽  
Repetitive Motion ◽  
Primal Dual

Tri-Criteria Optimization Motion Planning at Acceleration-Level of Dual Redundant Manipulators

Robotica ◽  
2019 ◽  
Vol 38 (6) ◽  
pp. 983-999
Author(s):  
Zhaoli Jia ◽  
Siyuan Chen ◽  
Zhijun Zhang ◽  
Nan Zhong ◽  
Pengchao Zhang ◽  
...  
Keyword(s):  
Motion Planning ◽  
Joint Angle ◽  
Weighting Factor ◽  
Quadratic Program ◽  
Redundant Manipulators ◽  
Repetitive Motion ◽  
Acceleration Level ◽  
Primal Dual ◽  
Joint Velocity ◽  
Joint Acceleration

SUMMARYIn order to solve joint-angle drift problem of dual redundant manipulators at acceleration-level, an acceleration-level tri-criteria optimization motion planning (ALTC-OMP) scheme is proposed, which combines the minimum acceleration norm, repetitive motion planning, and infinity-norm acceleration minimization solutions via weighting factor. This scheme can resolve the joint-angle drift problem of dual redundant manipulators which will arise in single criteria or bi-criteria scheme. In addition, the proposed scheme considers joint-velocity joint-acceleration physical limits. The proposed scheme can not only guarantee joint-velocity and joint-acceleration within their physical limits, but also ensure that final joint-velocity and joint-acceleration are near to zero. This scheme is realized by dual redundant manipulators which consist of left and right manipulators. In order to ensure the coordinated operation of manipulators, two motion planning problems are reformulated as two general quadratic program (QP) problems and further unified into one standard QP problem, which is solved by a simplified linear-variational-inequalities-based primal-dual neural network at the acceleration-level. Computer-simulation results based on dual PUMA560 redundant manipulators further demonstrate the effectiveness and feasibility of the proposed ALTC-OMP scheme to resolve joint-angle drift problem arising in the dual redundant manipulators.

Two/Infinity Norm Criteria Resolution of Manipulator Redundancy at Joint-Acceleration Level Using Primal-Dual Neural Network

2011 ◽  
Vol 14 (4) ◽  
pp. 1036-1046 ◽  
Author(s):  
Yu-Nong Zhang ◽  
Bing-Huang Cai ◽  
Jiang-Ping Yin ◽  
Lei Zhang
Keyword(s):  
Neural Network ◽  
Infinity Norm ◽  
Acceleration Level ◽  
Primal Dual ◽  
Joint Acceleration

Simultaneous repetitive motion planning of two redundant robot arms for acceleration-level cooperative manipulation

2013 ◽  
Vol 377 (34-36) ◽  
pp. 1979-1983 ◽  
Author(s):  
Yunong Zhang ◽  
Ying Wang ◽  
Dongsheng Guo ◽  
Xiaotian Yu ◽  
Lin Xiao
Keyword(s):  
Motion Planning ◽  
Repetitive Motion ◽  
Redundant Robot ◽  
Cooperative Manipulation ◽  
Acceleration Level ◽  
Robot Arms
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