A soft master-slave robot mimicking octopus arm structure using thin artificial muscles and wire encoders

Shota Furukawa, Shuichi Wakimoto, Takefumi Kanda, Hiroki Hagihara

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)


An octopus arm with a flexible structure and no rigid skeleton shows a high degree of freedom and flexibility. These excellent features are suitable for working in an environment having fragile and unknown-shaped objects. Therefore, a soft robot arm resembling an octopus arm can be useful as a harvesting machine without damaging crops in the agricultural field, as a rehabilitation apparatus in the welfare field, as a safe surgery tool in the medical field, and so on. Unlike industrial robots, to consider the applications of the soft robot arm, the instructions for it relating to a task cannot in many cases be given as a numerical value, and the motion according to an operator's sense and intent is useful. This paper describes the design and feedback control of a soft master-slave robot system. The system is configured with two soft rubber machines; one is a slave machine that is the soft robot arm mimicking the muscle arrangement of the octopus arm by pneumatic artificial muscles, and the other is a master machine that gives the target motion to the slave machine. Both are configured with soft materials. The slave machine has an actuating part and a sensing part, it can perform bending and torsional motions, and these motions are estimated by the sensing part with threads that connect to wire encoders. The master machine is almost the same configuration, but it has no actuating part. The slave machine is driven according to the deformation of the master machine. We confirmed experimentally that the slave machine followed the master machine that was deformed by an operator.

Original languageEnglish
Article number40
Issue number2
Publication statusPublished - Jun 1 2019


  • Artificial muscle
  • Master-slave arm
  • Octopus arm
  • Soft robot arm

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Control and Optimization


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