IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v144y2018icp91-107.html
   My bibliography  Save this article

High performance rigid body simulation of modularized robots using constraint-based models

Author

Listed:
  • Sobehart, Lionel
  • Harada, Hiroyuki

Abstract

Modularization using self-controlling servo-motors allows for rapid prototyping of highly articulated robots at a much lower cost than custom designs. Microcontrollers within the motor casings allow the internal motor to be controlled in a closed loop running at a much higher frequency than possible with external commands, at the cost of an inability to use directly estimated motor responses, especially when internal components are not known. Although electro-mechanical motor models have been used to simulate systems directly when the module components are known, this requires full knowledge of the system and small steps during discrete time simulation to prevent instabilities in the simulation and control. We propose a rigid body constraint based model for the simulation of internally controlled articulated robot modules that can reduce simulation instabilities at larger time-steps without requiring simulation specific non-physical damping or closed form dynamic solutions. This method uses the properties of rigid body constraints to limit system dynamics when low system inertia or high control gains would otherwise result in physically impossible performance. In practice, the simulation accuracy of this method is comparable to traditional models, but an order of magnitude faster in practice due to larger time-steps and improved range of stability.

Suggested Citation

  • Sobehart, Lionel & Harada, Hiroyuki, 2018. "High performance rigid body simulation of modularized robots using constraint-based models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 144(C), pages 91-107.
  • Handle: RePEc:eee:matcom:v:144:y:2018:i:c:p:91-107
    DOI: 10.1016/j.matcom.2017.07.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475417302744
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.matcom.2017.07.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Akdağ, M. & Karagülle, H. & Malgaca, L., 2012. "An integrated approach for simulation of mechatronic systems applied to a hexapod robot," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(5), pages 818-835.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jin, Jie & Chen, Weijie & Qiu, Lixin & Zhu, Jingcan & Liu, Haiyan, 2023. "A noise tolerant parameter-variable zeroing neural network and its applications," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 207(C), pages 482-498.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Javier Velasco & Isidro Calvo & Oscar Barambones & Pablo Venegas & Cristian Napole, 2020. "Experimental Validation of a Sliding Mode Control for a Stewart Platform Used in Aerospace Inspection Applications," Mathematics, MDPI, vol. 8(11), pages 1-15, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:matcom:v:144:y:2018:i:c:p:91-107. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.