Development of Integrated Innovation Experiment Platform Based on 3- PRS Parallel Mechanism

Title:Development of Integrated Innovation Experiment Platform Based on 3- PRS Parallel Mechanism

Volume: 14 Issue: 3

Author(s): Guoqiang Chen*, Hongpeng Zhou, Junjie Huang, Feng Jiao, Hanchao Li and Zhenzhen Liu

Affiliation:

• School of Mechanical and Power Engineering, Henan Polytechnic University, Jiaozuo 454000,China

Keywords: 3-PRS parallel mechanism, binocular vision, BPNN, control strategy, integrated innovation experiment platform, regression CNN.

Abstract:

Background: The parallel mechanism plays an important role in various fields. The multifunctional integrated innovation experiment platform can improve the utilization rate of the mechanism and be applied in many fields.

Objective: The main objective of the study is to establish an integrated innovation experiment platform based on the 3-PRS parallel mechanism, which can be used in typical application and related technology development.

Methods: The integrated innovation experiment platform is established and analyzed based on the 3-PRS parallel mechanism. According to the 3D model of the experiment platform, the kinematics and dynamics are analyzed. The force/position control strategy of the system is adopted. According to the function of the experiment platform, two kinds of application and the position and pose measurement technology are developed. The experiment platform is developed by the following methods: (1) The XY table is set up on the fixing platform of the 3-PRS parallel mechanism, so that the mechanism has five degrees of freedom, and the many kinds of workpiece can be easily processed. (2) By selecting the impedance parameter, the experiment platform can realize the compliant control of plantar flexion/dorsiflexion and varus/eversion simultaneously. (3) The binocular vision position and pose measurement method is used to obtain the marked images of the experiment platform through dual cameras, and the position and pose is obtained through image processing, 3D reconstruction and stereo matching, etc. (4) The position and pose detection based on deep learning is divided into two parts: one is to detect the slider height using the regression Convolutional Neural Network (CNN); the other is to compute the position and pose using the Back Propagation Neural Network (BPNN).

Results: The experiment results show that the function of the 3-PRS parallel mechanism integrated innovation experiment platform can be effectively realized. The position and pose can be accurately measured in real time using the proposed two measurement methods. The impedance parameters are selected to achieve the rehabilitation training function of the 3-PRS ankle rehabilitation robot and the characters are processed to verify the function of the 3-PRS-XY series-parallel machine tool.

Conclusion: The integrated innovation experiment platform based on the 3-PRS parallel mechanism can achieve the function of mechanical processing and rehabilitation training, and can also measure the state of motion in real time through machine vision and deep learning.

Cite this article as:

Chen Guoqiang *, Zhou Hongpeng , Huang Junjie , Jiao Feng , Li Hanchao and Liu Zhenzhen , Development of Integrated Innovation Experiment Platform Based on 3- PRS Parallel Mechanism, Recent Patents on Mechanical Engineering 2021; 14 (3) . https://dx.doi.org/10.2174/2212797613999201228202533