Research Papers

Generating Robot Trajectories for Conformal Three-Dimensional Printing Using Nonplanar Layers

[+] Author and Article Information
Aniruddha V. Shembekar, Yeo Jung Yoon, Alec Kanyuck

Center for Advanced Manufacturing,
University of Southern California,
Los Angeles, CA 90007

Satyandra K. Gupta

Center for Advanced Manufacturing,
University of Southern California,
Los Angeles, CA 90007
e-mail: guptask@usc.edu

1Corresponding author.

Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received September 25, 2018; final manuscript received February 26, 2019; published online April 1, 2019. Assoc. Editor: Yan Wang.

J. Comput. Inf. Sci. Eng 19(3), 031011 (Apr 01, 2019) (13 pages) Paper No: JCISE-18-1265; doi: 10.1115/1.4043013 History: Received September 25, 2018; Revised February 26, 2019

Additive manufacturing (AM) technologies have been widely used to fabricate three-dimensional (3D) objects quickly and cost-effectively. However, building parts consisting of complex geometries with curvatures can be a challenging process for the traditional AM system whose capability is restricted to planar layered printing. Using six degrees-of-freedom (DOF) industrial robots for AM overcomes this limitation by allowing the material deposition to take place on nonplanar surfaces. In this paper, we present trajectory planning algorithms for 3D printing using nonplanar material deposition. Trajectory parameters are selected to avoid collision with printing surface and satisfy robot constraints. We have implemented our approach by using a 6DOF robot arm. The complex 3D structures with various curvatures were successfully fabricated with a good surface finish.

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Fig. 1

(a) Hatching along 20 deg slope, (b) hatching along 40 deg slope, (c) hatching along 60 deg slope, and (d) hatching along 90 deg slope

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Fig. 2

Tool path generation of nonplanar layers with varying hatching angle

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Fig. 3

Illustration of path consistency challenges during moving from P1 to P2. Robot configurations Θ2 and Θ2′ can reach P2. Going from Θ1 to Θ2 leads to a consistent path. Going from Θ1 to Θ2′ leads to an inconsistent path.

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Fig. 4

Representative cone generation for waypoints along the tool path

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Fig. 5

Changes in TCP orientation along a planar, convex and concave surface

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Fig. 6

Printing along a curved surface: (a) without velocity control and (b) with velocity control

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Fig. 7

(a) Damaged base and (b) printed model of scaled down version of car bonnet

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Fig. 8

(a) Squeezed out excess material and (b) curling of hatching lines along a layer

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Fig. 9

Position of TCP and end effector with respect to flange frame coordinate

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Fig. 11

robotstudio simulation to check the generated trajectory

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Fig. 12

Flowchart of printing process

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Fig. 13

Experimental setups of robotic AM system

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Fig. 14

The path with the zigzag pattern is generated on the nonplanar surface

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Fig. 15

Specimens of different sizes and shapes

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Fig. 16

Nonplanar 3D Printing of (a) specimen A, (b) specimen C, and (c) specimen E

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Fig. 17

Three-dimensional CAD models and physical models printed by the robotic 3D printing system: specimens A–F

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Fig. 18

Surface roughness measurement locations 1–5 for each specimen A–E

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Fig. 19

(a) Surface finish comparison between specimen Aplanar (left) and specimen A (right), (b) specimen Cplanar printed by the traditional 3D printer using planar layered method, (c) enlarged pictures of specimen Cplanar (left) and specimen C (right)



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