Published: 2017-07-04
ISBN: 978-91-7685-575-1
ISSN: 1650-3686 (print), 1650-3740 (online)
The paper’s primary goal is to develop a mathematical model that could be used towards the development and improvement of orthotic assist gloves. The model is constructed using component based modeling in the object-oriented declarative language Modelica, specifically the MultiBody Modelica library. Multiple hand models currently do exist; however, they are mainly causal, and require separate development and validation of mathematical solvers before use. By using Modelica, the model is constructed from the system’s physical equations, thereby relieving issues regarding validity of the model’s computational equations; the acausality inherent in Modelica allows for model development that more closely mirrors relations in the physical world. The model is scoped to be able to model the kinematics and dynamics of the hand when grasping a spherical object – both bone structure and muscle geometry and actuation are simplifications based off anatomy literature. The contact model is developed as a separate component from the hand system. The main design goal of the contact model is to represent the characteristics of a relatively rigid object that still maintains a degree of friction and pliability on the surface layer.
The main two grasps tested in the paper are the prehensile and precision grasps (powerful and dexterous grasps). The muscle actuation profiles per each finger are adjusted until the desired dynamic profile is achieved for each type of grasp. The main data points of interests are the joint angles and contact forces for each finger. Further verification of the model is done using the animation automatically generated by the tool. Simulation testing results indicate that the model can successfully simulate contractions at all levels of abstraction of the hand’s components (basic bone-joint components, finger components, and the overall hand system). The results also indicate that both prehensile and precision grasps are possible, given appropriate muscle actuation and finger orientation parameter values.
Cutkosky, M. R., & Howe, R. D. (1990). Human Grasp Choice and Robotic Grasp Analysis. In S. T. Venkataraman & T. Iberall (Eds.), Dextrous Robot Hands (pp. 5-31). Springer-Verlag.
Griffin, W. B., Findley, R. P., Turner, M. L., & Cutkosky, M. R. (2000). Calibration and Mapping of a Human Hand for Dexterous Telemanipulation. ASME IMECE 2000 Conference Haptic Interfaces for Virtual Environments and Teleoperator Systems Symposium. Retrieved from http://wwwcdr.stanford.edu/DML/publications/griffin_asme00.pdf
Adler A, “GM-NASA Space Robot Partnhership brings “Power” Glove to Life”, GM Corporate News announcement, 2017 July 6th, http://media.gm.com/media/us/en/gm/home.detail.html/content/Pages/news/us/en/2016/jul/0706-gm-nasa.html
Linn D. M., Ihrke A. C., Diftler M. A., “Human grasp assist device and method of use”, US Patent No. 8255079 B2, 2012.
Polygerinos P, , Galloway K. C., Savage E., Herman M., O’ Donnell K, and Walsh J. C., “Soft Robotic Glove for Hand Rehabilitation and Task Specific Training”, 2015 IEEE International Conference on Robotics and Automation, May 2015, doi: https://doi.org/10.1109/ICRA.2015.7139597
Yanchev T, “Power Assist Gloves”, https://www.youtube.com/watch?v=gzfZCTYREww 2015
van Nierop, O. A., van der Helm, A., Overbeeke, K. J., & Djajadiningrat, T. J.P. (2007). A natural human hand model. The Visual Computer, 24(1). https://doi.org/10.1007/s00371-007-0176-x
Gustus, A., Stillfried, G., Visser, J., Jörntell, H., & van der Smagt, P. (2012). Human hand modelling: kinematics, dynamics, applications. Biological Cybernetics, 106(11). https://doi.org/10.1007/s00422-012-0532-4
Wan Tarmizi, W. F. B., Elamvazuthi, I., & Begam, M. (2009). Kinematic and Dynamic Modeling of a MultiFingered robot Hand. International Journal of Basic & Applied Sciences, 9(10). Retrieved from http://ijens.org/index.htm
Marieb, E. N. (2000). Essentials of human anatomy and physiology (6th ed.). San Francisco: Benjamin Cummings. Otter, M., Elmquist H, Mattson S. E., “The New Modelica Multibody Library”, Proceedings of the 3rd International Modelica Conference, Linkopig, 2003
Tiller, M. (2014). Modelica by Example. Retrieved from http://book.xogeny.com/
Modelica® (2013) - A Unified Object-Oriented Language for Physical Systems Modeling, Language Specification https://modelica.org/documents/ModelicaSpec32Revision2.pdf
Hicks J. L., Uchida T.K., Seth A., Rajagopal A., Delp S.L., “Is my model good enough? Best practices for verification and validation of musculoskeletal models and simulation environment”, Journal of Bioengineering, Vol 137, Feb 2015.
Radder, B., Kottink AIR, van der Vaart N, et. al, “Usercentred input for a wearable soft-robotic glove supporting hand function in daily life”, 2015 IEEE International Conference on Rehabilitation Robotics (ICORR), Singapore, 2015, doi: https://doi.org/10.1109/ICORR.2015.7281249
Dymola (2017) Copyright © Dassault Systèmes, 1992-2016 http://www.3ds.com/productsservices/catia/products/dymola/
SystemModeler (2015) Copyright © 2015 Wolfram Research, Inc. http://wolfram.com/system-modeler/
OpenModelica (2016) Copyright Open Source Modelica Consortium (OSMC) https://www.openmodelica.org/
JModelica (2016) from http://jmodelica.org/
