A learning-based inverse kinematics solver for a multi-segment continuum robot in robot-independent mapping

Jiewen Lai, Kaicheng Huang, Henry K. Chu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Inverse kinematics (IK) is one of the most fundamental problems in robotics, as it makes use of the kinematics equations to determine the joint configurations necessary to reach a desired end-effector pose. In the field of continuum robot, solving the IK is relatively challenging, owing to kinematic redundancy with infinite number of solutions.In this paper, we present a simplified model to represent a multi-segment continuum robot using virtual rigid links. Based on the model, its IK can be solved using a multilayer perceptron (MLP), a class of feedforward neural network (FNN). The transformation between virtual joint space to task space is described using Denavit-Hartenberg (D-H) convention. Using 20, 000 established training data for supervised learning, the MLP reaches a mean squared error of 0.022 for a dual-segment continuum robot. The trained MLP is then used to find the joints for different end-effector positions, and the results show a mean relative error of 2.90% can be on the robot configuration. Hence, this simplified model and its MLP provide a simple method to evaluate the IK solution of a two-segment continuum robot, which can also be further generalized and implemented in multi-segment cases.

Original languageEnglish
Title of host publicationIEEE International Conference on Robotics and Biomimetics, ROBIO 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages576-582
Number of pages7
ISBN (Electronic)9781728163215
DOIs
Publication statusPublished - Dec 2019
Event2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019 - Dali, China
Duration: 6 Dec 20198 Dec 2019

Publication series

NameIEEE International Conference on Robotics and Biomimetics, ROBIO 2019

Conference

Conference2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019
Country/TerritoryChina
CityDali
Period6/12/198/12/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Hardware and Architecture
  • Mechanical Engineering
  • Control and Optimization

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