Acquisition of a page turning skill for a multifingered hand using reinforcement learning

Authors: Ueda J.; Negi R.; Yoshikawa T.

Source: Advanced Robotics, Volume 18, Number 1, 2004 , pp. 101-114(14)

Publisher: VSP, an imprint of Brill

Buy & download fulltext article:

OR

Price: $35.00 plus tax (Refund Policy)

Abstract:

This paper proposes a method of acquisition of a page turning skill for a multifingered robotic hand using reinforcement learning. The goal of this paper is generation of the manipulation skill of a flexible object without its explicit model and tactile sensation during its control. In this paper, a page turning task is considered as an example of such tasks, where a sheet of paper, generally used in books, is a flexible object. The fingertip trajectories are obtained by reinforcement learning based on simulation. The reward considering a friction condition is given, so that a page turning skill without slip between the finger and the paper is obtained. The validity is confirmed by an experimental system which consists of a 2-d.o.f. manipulator and two 2-d.o.f. fingers.
Related content

Tools

Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content

Text size:

A | A | A | A
Share this item with others: These icons link to social bookmarking sites where readers can share and discover new web pages. print icon Print this page