Shashank Swaminathan
Novi, Michigan, USA
Johan Andreasson
Modelon KK, Japan
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http://dx.doi.org/10.3384/ecp17132745Published in: Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017
Linköping Electronic Conference Proceedings 43:81, p. 745-754
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.
