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IJAT Vol.15 No.5 pp. 669-677
doi: 10.20965/ijat.2021.p0669
(2021)

Paper:

Imitation Learning System Design with Small Training Data for Flexible Tool Manipulation

Harumo Sasatake*,†, Ryosuke Tasaki**, Takahito Yamashita**, and Naoki Uchiyama*

*Toyohashi University of Technology
1-1 Tempaku-cho, Toyohashi, Aichi 441-8580, Japan

Corresponding author

**Aoyama Gakuin University, Sagamihara, Japan

Received:
February 26, 2021
Accepted:
April 26, 2021
Published:
September 5, 2021
Keywords:
system integration, tool manipulation, imitation learning, deep learning, human support robot
Abstract

Population aging has become a major problem in developed countries. As the labor force declines, robot arms are expected to replace human labor for simple tasks. A robotic arm attaches a tool specialized for a task and acquires the movement through teaching by an engineer with expert knowledge. However, the number of such engineers is limited; therefore, a teaching method that can be used by non-technical personnel is necessitated. As a teaching method, deep learning can be used to imitate human behavior and tool usage. However, deep learning requires a large amount of training data for learning. In this study, the target task of the robot is to sweep multiple pieces of dirt using a broom. The proposed learning system can estimate the initial parameters for deep learning based on experience, as well as the shape and physical properties of the tools. It can reduce the number of training data points when learning a new tool. A virtual reality system is used to move the robot arm easily and safely, as well as to create training data for imitation. In this study, cleaning experiments are conducted to evaluate the effectiveness of the proposed method. The experimental results confirm that the proposed method can accelerate the learning speed of deep learning and acquire cleaning ability using a small amount of training data.

Cite this article as:
Harumo Sasatake, Ryosuke Tasaki, Takahito Yamashita, and Naoki Uchiyama, “Imitation Learning System Design with Small Training Data for Flexible Tool Manipulation,” Int. J. Automation Technol., Vol.15, No.5, pp. 669-677, 2021.
Data files:
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Last updated on Sep. 24, 2021