Literature DB >> 25969947

Modal kinematics for multisection continuum arms.

Isuru S Godage1, Gustavo A Medrano-Cerda, David T Branson, Emanuele Guglielmino, Darwin G Caldwell.   

Abstract

This paper presents a novel spatial kinematic model for multisection continuum arms based on mode shape functions (MSF). Modal methods have been used in many disciplines from finite element methods to structural analysis to approximate complex and nonlinear parametric variations with simple mathematical functions. Given certain constraints and required accuracy, this helps to simplify complex phenomena with numerically efficient implementations leading to fast computations. A successful application of the modal approximation techniques to develop a new modal kinematic model for general variable length multisection continuum arms is discussed. The proposed method solves the limitations associated with previous models and introduces a new approach for readily deriving exact, singularity-free and unique MSF's that simplifies the approach and avoids mode switching. The model is able to simulate spatial bending as well as straight arm motions (i.e., pure elongation/contraction), and introduces inverse position and orientation kinematics for multisection continuum arms. A kinematic decoupling feature, splitting position and orientation inverse kinematics is introduced. This type of decoupling has not been presented for these types of robotic arms before. The model also carefully accounts for physical constraints in the joint space to provide enhanced insight into practical mechanics and impose actuator mechanical limitations onto the kinematics thus generating fully realizable results. The proposed method is easily applicable to a broad spectrum of continuum arm designs.

Mesh:

Year:  2015        PMID: 25969947     DOI: 10.1088/1748-3190/10/3/035002

Source DB:  PubMed          Journal:  Bioinspir Biomim        ISSN: 1748-3182            Impact factor:   2.956


  1 in total

1.  How to Model Tendon-Driven Continuum Robots and Benchmark Modelling Performance.

Authors:  Priyanka Rao; Quentin Peyron; Sven Lilge; Jessica Burgner-Kahrs
Journal:  Front Robot AI       Date:  2021-02-02
  1 in total

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