Research Papers

A New Approach to Design of a Lightweight Anthropomorphic Arm for Service Applications

[+] Author and Article Information
Lelai Zhou

Department of Mechanical
and Manufacturing Engineering,
Aalborg University,
Aalborg 9220, Denmark
e-mail: lzh@m-tech.aau.dk

Shaoping Bai

Associate Professor
Department of Mechanical
and Manufacturing Engineering,
Aalborg University,
Aalborg 9220, Denmark
e-mail: shb@m-tech.aau.dk

1Corresponding author.

Contributed by the Mechanisms and Robotics Committee of ASME for publication in the JOURNAL OF MECHANISMS AND ROBOTICS. Manuscript received June 14, 2012; final manuscript received August 1, 2014; published online December 4, 2014. Assoc. Editor: Xianmin Zhang.

J. Mechanisms Robotics 7(3), 031001 (Aug 01, 2015) (12 pages) Paper No: JMR-12-1073; doi: 10.1115/1.4028292 History: Received June 14, 2012; Revised August 01, 2014; Online December 04, 2014

This paper describes a new approach to the design of a lightweight robotic arm for service applications. A major design objective is to achieve a lightweight robot with desired kinematic performance and compliance. This is accomplished by an integrated design optimization approach, where robot kinematics, dynamics, drive-train design and strength analysis by means of finite element analysis (FEA) are generally considered. In this approach, kinematic dimensions, structural dimensions, and the motors and the gearboxes are parameterized as design variables. Constraints are formulated on the basis of kinematic performance, dynamic requirements and structural strength limitations, whereas the main objective is to minimize the weight. The design optimization of a five degree-of-freedom (dof) lightweight arm is demonstrated and the robot development for service application is also presented.

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Fig. 1

Conceptual design of a 5 dof lightweight anthropomorphic arm

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Fig. 2

Robotic arm coordinate system

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Fig. 3

Dimensional parameters of the robotic arm

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Fig. 4

Schematic view of drive-train model for a single joint

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Fig. 6

Functional modules of the integrated optimization approach

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Fig. 5

Illustration of the complex method

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Fig. 7

Boundary conditions of the FEA model

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Fig. 8

Diagram of the optimization routine

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Fig. 9

Plots of the trajectories

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Fig. 11

Convergence plots for the design variables of motors and gearboxes

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Fig. 17

User interface of the robotic arm control

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Fig. 14

Motor torques for initial and optimal drive-train combinations. (a) Joint 1 and (b) Joint 2.

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Fig. 10

Convergence of the weight of the robotic arm

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Fig. 16

Control system of the robotic arm

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Fig. 12

Convergence of dimensional variables. (a) Link length ratio, (b) wh1 and wh2, and (c) ra and rb.

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Fig. 13

von-Mises element stress in the original (top) and optimized (bottom) robotic arm

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Fig. 15

Prototypes of the robot arm. (a) First prototype and (b) second prototype for drink serving (demo video in Ref. [25]).




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