Analysis of Open Architecture 6R Robot Forward and Inverse Kinematics Adaptive to Structural Variations

Wang, Chong; Liu, Dongxue; Sun, Qun; Wang, Tong

doi:10.1155/2021/4516109

Cited by 6 publications

(8 citation statements)

References 17 publications

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“…The time complexity of the algorithm ω is O ( n ), which is the same as the traditional algorithm Trad 12,13 and the algorithm ω . Theoretically, when it tends to infinity, the execution efficiency of the three algorithms is the same.…”

Section: Simulation Results and Discussionmentioning

confidence: 94%

“…Only joint stroke is considered T(n) represents the execution time of the code; n represents the size of the data size; f(n) represents the total number of executions per line; O represents the trend of code execution time with the increase of data scale, also known as progressive time complexity. The time complexity of the algorithm v is O(n), which is the same as the traditional algorithm Trad 12,13 and the algorithm v. Theoretically, when it tends to infinity, the execution efficiency of the three algorithms is the same.…”

Section: Weightmentioning

confidence: 94%

“…11 Therefore, choosing appropriate joint variables is the premise of trajectory planning. Wang et al 12,13 used the principle of ''shortest stroke'' to select a group of joint variables with the smallest variation of front and rear joint angle as the optimal solution. Zhao et al 14 took the principle of ''moving more small joints and fewer large joints'' as the influencing factor of the current joint angle, so as to select the optimal solution of the inverse solution.…”

Section: Introductionmentioning

confidence: 99%

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Cartesian space track planning for welding robot with inverse solution multi-objective optimization

Cheng

Yang

et al. 2022

Measurement and Control

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Aiming at the problem that the traditional inverse solution optimization method is not comprehensive and does not consider the robot structure and actual working conditions, an inverse solution multi-objective optimization method is proposed. This method comprehensively considers the structural size and working state of the welding robot, establishes the stiffness performance evaluation index, optimizes the performance index of the subsequent connecting rod movement area caused by joint rotation, and selects the optimal inverse solution combined with the principle of “minimum joint displacement.” Compared with the traditional method, this method is more comprehensive. It makes the variation range of the rear three small joints of the welding robot larger than the front three large joints, which reduces the power consumption. In addition, it also improves the stiffness of the welding robot at the trajectory point, which ensures the reliability of the welding robot. On this basis, for linear and arc welds, the position interpolation of cartesian space line and arc trajectory based on the S-shaped acceleration and deceleration curve and the posture interpolation of spherical linear interpolation based on unit quaternion are realized. MATLAB simulation results show that the combination of the inverse optimization method and the interpolation method makes the end trajectory, velocity, acceleration, posture curve, and joint displacement curve of the welding robot continuous, smooth, and without mutation.

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Section: Simulation Results and Discussionmentioning

confidence: 94%

Section: Weightmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cartesian space track planning for welding robot with inverse solution multi-objective optimization

Cheng

Yang

et al. 2022

Measurement and Control

View full text Add to dashboard Cite

show abstract

“…Two coordinate systems are transformed when they coincide at the origin but have different states. Joint transformation is the combination of translation transformation and rotation transformation, which can be used to transform coordinates with different states and positions [14], [15]. The relevant coordinate translations for translation, rotation, and joint transformation are shown in Equation (1).…”

Section: A Kinematics and Tp Of Rehabilitation Robotmentioning

confidence: 99%

“…It can optimize the random locations of flight, reduce runtime overhead, and enhance the convergence rate. The relevant expression is shown in Equation (14).…”

Section: B Csa Algorithm Process Design Integrating Multi-objective T...mentioning

confidence: 99%

Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA Algorithm

Xia

2023

IEEE Access

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With the aging global population, there are more patients with hemiplegia caused by stroke. The demand for rehabilitation robots to assist rehabilitation therapists is also increasing. To solve the above problems, a reasonable trajectory planning of the rehabilitation robot joints is constructed to achieve rehabilitation assistance, improve safety and practicality.Firstly, a Kinematics model is constructed, and B-spline is applied to realize the trajectory planning of the rehabilitation robot. By introducing crow search algorithm and multiple crow search algorithms, the energy impact multi-objective optimization for the upper limb movement of the rehabilitation robot is carried out. Relevant experiments are designed to compare and verify the optimization effects of the algorithms. From the results, by optimizing the crow search algorithm, only 25.36% and 34.20% of the impact and energy are used. The average impact size per unit of time decreases by 74.68%. The energy consumption per unit time decreases by 65.39%.After optimizing the crow search algorithm, the impact and energy per unit time are only 14.41% and 17.25%, respectively. The energy per unit time decreases by 74.53%, and the impact decreases by 82.97%. Compared with other algorithms, the space complexity of the improved method is very small, and the standard deviation is 0.03. The optimization algorithm performs well in trajectory planning optimization. It is of great significance in the trajectory planning and rehabilitation role of rehabilitation robots.

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Structure Design and Simulation Test of Water Jet Grassland Root-Cutting Machine

et al. 2023

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Root-cutting is one of the effective methods to improve degraded grassland. It mainly increases the contact area between roots and oxygen by cutting off the transverse roots of vegetation inside the soil, and thus achieve the purpose of restoring growth. However, the hanging cutter head root-cutting method commonly used at present has the problems of large cutting resistance and high soil disturbance rate during operation. Therefore, a water jet grassland root-cutting machine is designed to improve the shortcomings of the previous method. This method does not need to go deep into the soil and is not affected by the internal resistance of the soil, and the water flow has a positive recovery effect on the grassland, paying more attention to the environmental awareness of the grassland. For the design of this machine, the structure and working principle of it is overall structure and key components are analyzed. The motion attitude of the profiling mechanism was analyzed by modified D-H (MDH) method. The dynamic model of the root-cutting machine and the obstacle avoidance model of the profiling mechanism were established by Lagrange function. With the help of MATLAB/Simulink components, the operation process of the root-cutting machine in different ground was simulated. Results showed: In the process of root-cutting operation, the water jet grassland root-cutting machine has a good adaptability in sinusoidal ground and irregular smooth ground. In the ground environment of sharp mutation, it can satisfy the adaptability to the ground through the obstacle avoidance operation of the profiling mechanism. The water jet grassland root-cutting machine designed in this paper can improve the efficiency of grassland restoration and meet the stability requirements of operation in different terrains.INDEX TERMS Dynamics, profiling mechanism, root-cutting machine, structural design, SimMechanics.

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Analysis of Open Architecture 6R Robot Forward and Inverse Kinematics Adaptive to Structural Variations

Cited by 6 publications

References 17 publications

Cartesian space track planning for welding robot with inverse solution multi-objective optimization

Cartesian space track planning for welding robot with inverse solution multi-objective optimization

Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA Algorithm

Structure Design and Simulation Test of Water Jet Grassland Root-Cutting Machine

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