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Research Papers: Design of Mechanisms and Robotic Systems

Unified Kinematics Analysis and Low-Velocity Driving Optimization for Parallel Hip Joint Manipulator

[+] Author and Article Information
Song-Tao Wang

Automotive Engineering Department,
Chengde Petroleum College,
Chengde University Park,
Chengde, Hebei 067000, China;
School of Mechanical and Electrical Engineering,
China University of Mining and Technology,
No. 1, University Road,
Xuzhou, Jiangsu 221116, China
e-mail: santeer@foxmail.com

Gang Cheng

School of Mechanical and Electrical Engineering,
China University of Mining and Technology,
No. 1, University Road,
Xuzhou, Jiangsu 221116, China
e-mail: chg@cumt.edu.cn

De-Hua Yang

National Astronomical Observatories/Nanjing
Institute of Astronomical Optics and Technology,
Chinese Academy of Sciences,
No. 188, Bancang Street,
Nanjing, Jiangsu 210042, China
e-mail: dhyang@niaot.ac.cn

Jian-Hua Yang

School of Mechanical and Electrical Engineering,
China University of Mining and Technology,
No. 1, University Road,
Xuzhou, Jiangsu 221116, China
e-mail: jianhuayang@cumt.edu.cn

1Corresponding author.

Contributed by the Mechanisms and Robotics Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received September 15, 2014; final manuscript received April 17, 2015; published online June 8, 2015. Assoc. Editor: Matthew B. Parkinson.

J. Mech. Des 137(8), 082301 (Aug 01, 2015) (11 pages) Paper No: MD-14-1581; doi: 10.1115/1.4030433 History: Received September 15, 2014; Revised April 17, 2015; Online June 08, 2015

Unified modeling for the kinematics analysis of a parallel hip joint manipulator (PHJM) is proposed, and structural parameters of the PHJM are optimized based on the unified model for obtaining low-velocity driving performance. Based on the finite element theory, a unified model for kinematics analysis is established, and the Monte Carlo method is subsequently proposed to solve the workspace for the PHJM. To optimize the workspace, a 6 surface-14 point (6 S-14 P) method is proposed to judge whether the workspace includes the task space. The structural parameters are further optimized to obtain low-velocity driving performance, and the motion performances of the PHJM with the optimal parameter are numerically simulated. The velocity simulation results demonstrate that the maximum relative velocity of the PHJM with the optimal parameter decreases by 23.2%. The unified kinematics analysis and low-velocity driving optimization effectively improve the performance for the PHJM and enrich the optimization theory for parallel manipulators with high velocities and given tasks.

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References

Figures

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Fig. 1

The PHJM: (a) prototype of the PHJM and (b) topology of the PHJM

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Fig. 2

Motive rule of the PHJM

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Fig. 3

Task-space of the PHJM

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Fig. 4

Schematic view of the task-space and workspace: (a) task-space and workspace and (b) projection of the two spaces

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Fig. 7

Workspace optimization flow

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Fig. 8

Low-velocity driving optimization flow

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Fig. 9

Workspace and task-space projection: (a) γ = 25 deg projection, (b) γ = −25 deg projection, (c) β = 10 deg projection, (d) β = 10 deg projection, (e) α = 10 deg projection, and (f) α = 10 deg projection

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Fig. 10

Driving velocity results: (a) velocity of driving leg 1, (b) velocity of driving leg 2, and (c) velocity of driving leg 3

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