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MATLAB/Simulink Based Rapid Control Prototyping for Multivendor Robot Applications Christina Deatcu*, Birger Freymann, Artur Schmidt, Thorsten Pawletta Hochschule Wismar – University of Applied Sciences: Technology, Business and Design, Research Group Computational Engineering and Automation, Philipp-Müller-Straße 14, 23966 Wismar, Germany *[email protected]

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Abstract. Industrial robots are used in various fields of application and many robot manufacturers are active in the market. In most cases, their software solutions are proprietary and, consequently, they cannot be used for third party robots. Moreover, the integration of external hard- or software is highly restricted. Long term standardization efforts for robot programming languages, such as the Industrial Robot Language (IRL) and its successor, the Programming Language for Robots (PLR), have been mostly ignored by robot manufacturers. This fact leads to a restriction on the combined usage of robots. Multi-robot applications where robots have to interact are usually limited to software solutions and robots of one manufacturer. On the other hand, control design in engineering is often carried out by the usage of Scientific and Technical Computing Environments (SCEs) like MATLAB. The Robotic Control & Visualization Toolbox (RCV Tbx) for MATLAB/Simulink tries to close the gap between robot manufacturer-specific software solutions and SCEs. The current version of the RCV Tbx supports a uniform and integrated control development for KUKA and KAWASAKI robots in the MATLAB/Simulink environment. An extension to other robot types is straight forward. Thus, the implementation of heterogeneous multirobot applications is considerably simplified.

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 Figure 1: Adopted V-Model for Robot Control Development According to Maletzki [9].

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 Figure 3: Detailed V-Model for robot control development according to Maletzki [9].



 Figure 2: Conventional robot control development using vendor specific software.

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 Figure 5: A Multi-robot configuration with heterogeneous robot types using the RCV Tbx.

 Figure 4: Robot control programming with the RCV Tbx for MATLAB/Simulink.

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 Figure 6: Main parts of the RCV toolbox for MATLAB/Simulink.

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 Figure 7: Simplified interpreter algorithm.

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 Listing 1: Create and destroy robot objects.

 74 SNE 25(2) – 8/2015

rbrake() rcallback() rdisp() rerror() rget() ris() rkill()

rmove() robot() rpoint() rprocess() rreset() rrun() rset() rstatus() rstop() rteach() rwait()

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 Table 1: List of available robot control commands.

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Deatcu et al.

MATLAB/Simulink-based Rapid Control Prototyping 2.2 Part II: Robotic Visualization Tbx

>> load P1 P2 >> rprocess( {... Kuka, P1,... Kawasaki,{P2, 'speed', 50},... },... { Kuka, 'home',... Kawasaki, 'home',... } ); Listing 2: Two robots in a concurrent operation pro-grammed with rprocess().

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 Figure 9: Types of visualizable object.



 Figure 8: State-based control using Stateflow and RCV Tbx.

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Deatcu et al.

MATLAB/Simulink-based Rapid Control Prototyping

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ViSu.info

ViSu.create()

ViSu.repose_robot() ViSu.delete_robot()

ViSu.place_env() ViSu.repose_env()

ViSu.delete_env()

ViSu.place_part() ViSu.repose_part() ViSu.delete_part()

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2.3 Integrated RCV Tbx usage example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µSDUW¶ /LVWLQJLOOXVWUDWHVKRZ0$7/$%FRQWURODQGYLVXDOL ]DWLRQ LQVWDQFHV FDQ LQWHUDFW 0$7/$% FRPPDQGV LQ OLQHWRDQGKDYHWREHH[HFXWHGRQ WKHYLVXDOL]DWLRQLQVWDQFHZKLOHWKHLQGHQWHGOLQHV WRDQGDUHFRQWUROFRPPDQGVZKLFKKDYHWREH H[HFXWHGRQWKHFRQWUROLQVWDQFH   1 2 3 4 5 6 7

Table 2: User Interface for Visualization.

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8 9 10 11 12 13 14

>> ViSu.start; >> ViSu.create('Kawasaki', 40000,... [0,0,0,0,0,0]); >> r1=robot('open', 'Kawasaki',... 'tcpip', 'localhost', 40000); >> ViSu.create('Kuka', 40001,... [500,500,0,0,0,0]); >> r2=robot('open', 'Kuka',... 'tcpip', 'localhost', 40001); >> ViSu.place_env('table.stl',... [-800 0 0 0 0 0],'blue'); >> ViSu.place_part('test_tube.stl',... [-800 0 400 45 0 0],'white'); >> rset(r1,'signal', [-9, 10]); >> rmove(r1,'home2'); >> rmove(r2,'home2'); >> ViSu.info; >> ViSu.delete_part(1); >> robot(r1, r2, 'close'); >> ViSu.stop;

 Listing 3: Code Example of Interaction of the two Parts of RCV Tbx for MATLAB/Simulink.



76 SNE 25(2) – 8/2015

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Deatcu et al.

MATLAB/Simulink-based Rapid Control Prototyping

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 Figure 11: Visualization example after execution of some control commands.

 Figure 10: Visualization example after creation of objects.

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MATLAB/Simulink-based Rapid Control Prototyping

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