Abstract
The 4SPRR-SPR parallel robot, which has considerable potential for application in the field of machining, is a novel closed-loop mechanism with a high rigid-weight ratio. Kinematics and workspace analyses of the 4SPRR-SPR parallel robot are key requirements for its application in machining. In this study, the inverse kinematics of the 4SPRR-SPR parallel robot is analyzed using a geometric method based on the mechanism arrangement of the robot. The forward kinematics model is derived by training the vector-quantified temporal associative memory (VQTAM) network, which originates from a self-organizing map (SOM). Furthermore, an improved algorithm is obtained by combining the locally linear embedding (LLE) and VQTAM methods. A boundary extraction algorithm for the workspace analysis of the parallel robot is proposed. The performance of the boundary extraction algorithm is analyzed and compared with that of a global search algorithm; the result indicates that the novel algorithm has the same computational accuracy in addition to higher efficiency. The workspace of the 4SPRR-SPR parallel robot is analyzed using the boundary extraction algorithm. Finally, the 3D model of the 4SPRR-SPR parallel robot is simulated using the ADAMS software to verify the reliability of the proposed algorithms. The simulation results demonstrate the effectiveness of the methods proposed in this study. In addition, the robot kinematics and workspace analysis methods described herein can be extended to other serial and parallel robots. This research provides a theoretical framework for trajectory planning of mechanisms, workspace optimization of robots, and robotic control.
Highlights
Parallel robots offer noticeable advantages in machining applications, especially in the field of heavy equipment manufacture, due to their high rigid-weight ratio and load capacity
A majority of the aforementioned research studies are focused on the forward kinematics or motion control of a typical parallel mechanism (Stewart platform), which is of great significance to other related research on parallel robots
This paper describes a novel parallel robot that could be used as a mobile machining robot and proposes the forward kinematics of the 4SPRR-SPR parallel robots based on a vector-quantified temporal associative memory (VQTAM) neural network
Summary
Parallel robots offer noticeable advantages in machining applications, especially in the field of heavy equipment manufacture, due to their high rigid-weight ratio and load capacity. A majority of the aforementioned research studies are focused on the forward kinematics or motion control of a typical parallel mechanism (Stewart platform), which is of great significance to other related research on parallel robots. These studies indicate that the forward kinematics solution and control of parallel robots can be realized and obtained fairly accurately using an intelligent algorithm or machine learning. The arrangements of the kinematic pairs of the 4SPRR-SPR parallel robot are similar, except that the end of the first limb is fixed to the moving platform. The end effector can move along the X and Z axes
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
