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1. TOTO - tracking of thrown objects
2 years ago
The intention of this work is to create a new transport technique in manufacturing. In fully automated production systems, parts should be transported between workstations by robotic throwing and catching. There are two solution approaches to the transport-by-throwing task: aimed throwing (always hit the target) or active catching (tracking the catching device).

This is a successful first implementation of the active catching approach. Until now only tennis-balls are caught. A single standard gray-value camera observes the flight. An industrial gantry-robot tracks a mechanical gripper to a predicted interception position. This robot is realized at the Reinhold-Würth-University of the Heilbronn University in Künzelsau (Germany), in cooperation with the Institute of Computer Technology, TU Vienna (Austria).

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  • Blake Whitman staff 2 years ago
    god help us.
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  • Soxiam staff 2 years ago
    i am really really scared.
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  • Andrew Pile staff 2 years ago
    Hell yes!
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  • phantomcolor 2 years ago
    what kind of parts would you consider "throwable"? and would you consider the application best suited for long range throwing?
  • Dennis Barteit 2 years ago
    We are currently working on aimed throwing of cylindrical objects. The accuracy is good enough, so we don't need to track the catching device. This would be the desirable appplication: no additional tracking robot. However, in long range throwing (>4-5m) this would get more complicated to achieve. We are still searching for possible applications.
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  • Joe Moya plus 2 years ago
    So... has the robot been approached by the baseball sport agents? ...If not... it's only a matter of time.
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  • pekka tarvainen 2 years ago
    I remember our math teacher telling us a comparison between humans and future robots catching a ball; the computations were supposedly so complicated that a machine will probaby never be able to calculate so fast :-)
    Now, the things we presently consider improbable or downright impossible...
  • Dennis Barteit 2 years ago
    It is also good to prove that your teacher was wrong :-) And all the other people saying that this won't work...

    There is interesting research about human catching skills. For example, it was studied how field players in baseball "predict" a possible catching position. It is a rather simple strategy, that was also found to be used by dogs catching frisbees (I guess, it was the same strategy). A Japanese science lab already realized a free moving robot that catches balls using this strategy. The control of human interception movement is kept as simple as possible. Hence, it doesn't seem to be a big thing to adopt it to a robot. However, there are some problems...
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  • Evan Bassett 2 years ago
    I'm amused because I recognize the motors and cables used as being ones I work with every day.
  • Dennis Barteit 2 years ago
    We tried to use off-the-shelf industrial components.
  • Evan Bassett 2 years ago
    Makes sense. If you don't mind me asking, were they B&R controls? I mean obviously you have a PC in there somewhere doing the math with the camera, but I'm curious about the motion portion of the system.
  • Dennis Barteit 2 years ago
    Yes, a PC is used to detect the object in the image data, calculate the 3-D position, and predict the future flight trajectory. From this, an interception position is determined and the position information is sent to a Siemens SIMOTION motion controller (automation.siemens.com/_en/mc/mc-sol/en/2ea3f697-5b50-4d8f-b13f-80e338afad9f/index.aspx?c=r-simotion). The SIMOTION controls the movement of the robot's axes.
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  • Jason Hu 2 years ago
    Good job, Dennis. As I have done a similar robot, which kicks a throwing a ball up and down in a settled area, I wonder how you calibrated your ground coordinates with one camera. I mean the camera distortion might be a problem for such an accurate positioning device. How did you modify it?
  • Dennis Barteit 2 years ago
    Thanks, Jason. Of course, calibration is a problem with a fixed camera. I have some calibration sheets at the robot (you won't see them in the clip) for the determination of extrinsic camera parameters. Thus, the operational plane of the robot defines a world coordinate system. Calibration is done with the openCV library (sourceforge.net/projects/opencvlibrary/). Also the correction of radial and tangential distortion is done with openCV. However, the intrinsic camera parameters are obtained by the Matlab camera calibration toolbox and a couple of images of a calibration sheet (vision.caltech.edu/bouguetj/calib_doc/). The distortion is not that large, 'cause I use a 8.5 mm lens.
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  • bilderbuchi 2 years ago
    very nice work! *proud of TUW* :)
    i take it you know this video already: ebaumsworld.com/video/watch/80731612 ?
  • Dennis Barteit 2 years ago
    Yes, I know the robot hand of the Ishikawa Lab. They are doing really great work there. In the first publication, I know of them, in 2003, they presented a catching robot arm that could accelerate with 91G. It was equipped with a active stereo-vision system that could permanently track an object with 1000 fps. Really great work!
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  • Matthew Jackson 2 years ago
    Hi Dennis, I work for a press release company and have just stumbled across your video of TOTO, its amazing. I would love to write an article on your Robot. Could you please let me know who the main suppliers of your components are. In particular I'm looking for component manufacturers such as Festo, Bosch Rexroth or Rockwell Automation. I just need to check if we have clients who have supplied you with components, so that I can write the story. Contact me directly @ matthewj@cubicice.com Kind Regards Matt
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  • Just think, this tech used in manufacturing may result in new products being thrown around the plant. :>) Employees just trough part in machine.
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