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Research Papers

Robust Hybrid Position-Force Control for Robotic Surface Polishing

[+] Author and Article Information
J. Ernesto Solanes

Instituto de Diseño y Fabricación,
Universitat Politècnica de València,
Camí de Vera s/n,
València 46022, Spain,
e-mail: esolanes@idf.upv.es

Luis Gracia

Instituto de Diseño y Fabricación,
Universitat Politècnica de València,
Camí de Vera s/n,
València 46022, Spain
e-mail: luigraca@isa.upv.es

Pau Muñoz-Benavent

Instituto de Diseño y Fabricación,
Universitat Politècnica de València,
Camí de Vera s/n,
València 46022, Spain
e-mail: pmunyoz@disca.upv.es

Jaime Valls Miro

Centre for Autonomous Systems,
University of Technology Sydney,
Sydney 2007, NSW, Australia
e-mail: jaime.vallsmiro@uts.edu.au

Carlos Perez-Vidal

Ingeniería de Sistemas y Automática,
Universidad Miguel Hernández,
Avda de la Universidad s/n,
Elche 03202, Spain
e-mail: carlos.perez@umh.es

Josep Tornero

Instituto de Diseño y Fabricación,
Universitat Politècnica de València,
Camí de Vera s/n,
València 46022, Spain
e-mail: jtornero@isa.upv.es

1Corresponding author.

Manuscript received November 14, 2017; final manuscript received October 24, 2018; published online November 28, 2018. Assoc. Editor: Dragan Djurdjanovic.

J. Manuf. Sci. Eng 141(1), 011013 (Nov 28, 2018) (14 pages) Paper No: MANU-17-1707; doi: 10.1115/1.4041836 History: Received November 14, 2017; Revised October 24, 2018

This work presents a hybrid position-force control of robots for surface polishing using task priority. The robot force control is designed using sliding mode ideas in order to benefit from its inherent robustness and low computational cost. In order to avoid the chattering drawback typically present in sliding mode control, several chattering-free controllers are evaluated and tested. A distinctive feature of the method is that the sliding mode force task is defined using not only equality constraints but also inequality constraints, which are satisfied using conventional and nonconventional sliding mode control, respectively. Moreover, a lower priority tracking controller is defined to follow the desired reference trajectory on the surface being polished. The applicability and the effectiveness of the proposed approach considering the mentioned chattering-free controllers are substantiated by experimental results using a redundant 7R manipulator.

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References

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Figures

Grahic Jump Location
Fig. 1

Graphical comparison between conventional SMC (left) and nonconventional SMC (right)

Grahic Jump Location
Fig. 2

Experimental setup: 7R serial manipulator with a force sensor attached to the robot end-effector, a tool consisting of a cylinder and a flat rectangular plastic object as target

Grahic Jump Location
Fig. 3

Comparison of the constraint functions σi for the standard (dark blue) and chattering-free (light green) SMCs

Grahic Jump Location
Fig. 4

Comparison of the commutation functions for the standard (dark blue) and chattering-free (light green) SMCs

Grahic Jump Location
Fig. 5

Trajectory followed by the robot tool and circular reference trajectory (thick red line): left, standard SMC (dark blue); right, chattering-free SMC (light green)

Grahic Jump Location
Fig. 6

Frames of the video of the dynamic experiment: the time instant is indicated for each frame: (a) video: 0 m 33 s; graph: 21 s, (b) video: 1 m 15 s; graph: 63 s, (c) video: 2 m 02 s; graph: 110 s, (d) video: 2 m 06 s; graph: 114 s, (e) video: 4 m 13 s; graph: 241 s, and (f) video: 4 m 17 s; graph: 245 s

Grahic Jump Location
Fig. 7

Signals in the dynamic experiment as a function of time. First to fourth plots: original and modified constraint functions (σi in light cyan and ϕi in dark blue). Fifth plot: activation of the inequality constraint. Sixth plot: tool position {x, y, z} and reference signals {xref, yref}. Seventh plot: tool orientation {α, β, γ} in roll-pitch-yaw angles and reference signal γref. The reference signals are in solid thick line, {x, α} in thin dark line, {y, β} in thin light line, and {z, γ} in dashed line.

Grahic Jump Location
Fig. 8

Trajectory followed by the robot tool (thin blue line) and circular reference trajectory (thick red line): left, 3D representation; right, top view

Grahic Jump Location
Fig. 9

Frames of the video of the adaptation experiment: the time instant is indicated for each frame: (a) video: 0 m 19 s, (b) video: 0 m 55 s, (c) video: 1 m 22 s, (d) video: 1 m 33 s, (e) video: 1 m 40 s, and (f) video: 1 m 59 s

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