Curriculum-reinforcement learning on simulation platform of tendon-driven high-degree of freedom underactuated manipulator

Front Robot AI. 2023 Jul 12:10:1066518. doi: 10.3389/frobt.2023.1066518. eCollection 2023.

Abstract

A high degree of freedom (DOF) benefits manipulators by presenting various postures when reaching a target. Using a tendon-driven system with an underactuated structure can provide flexibility and weight reduction to such manipulators. The design and control of such a composite system are challenging owing to its complicated architecture and modeling difficulties. In our previous study, we developed a tendon-driven, high-DOF underactuated manipulator inspired from an ostrich neck referred to as the Robostrich arm. This study particularly focused on the control problems and simulation development of such a tendon-driven high-DOF underactuated manipulator. We proposed a curriculum-based reinforcement-learning approach. Inspired by human learning, progressing from simple to complex tasks, the Robostrich arm can obtain manipulation abilities by step-by-step reinforcement learning ranging from simple position control tasks to practical application tasks. In addition, an approach was developed to simulate tendon-driven manipulation with a complicated structure. The results show that the Robostrich arm can continuously reach various targets and simultaneously maintain its tip at the desired orientation while mounted on a mobile platform in the presence of perturbation. These results show that our system can achieve flexible manipulation ability even if vibrations are presented by locomotion.

Keywords: bio-inspired robot; curriculum learning; reinforcement learning; simulation; soft robotics; tendon-driven system; underactuated manipulator.

Grants and funding

This work was supported by the JSPS KAKENHI Grant Number JP18H05466 and JP20K19890.