International Journal of Automation Technology
Online ISSN : 1883-8022
Print ISSN : 1881-7629
ISSN-L : 1881-7629
Special Issue on Application of Robot and AI
Special Issue on Application of Robot and AI
Naoki Asakawa
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ジャーナル オープンアクセス

2021 年 15 巻 2 号 p. 139

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Due to changes in the global industrial structure, the number of employees in the manufacturing industry has decreased in developed countries. One of solutions to this situation offered in Industry 4.0 is “the utilization of robots and AI as alternatives to skilled workers.” This solution has been applied to various operations conventionally performed by skilled workers and has yielded consistent results. A skilled worker has two skills, namely, “physical operation skill” and “decision making skill,” which correspond to the utilization of robots and AI, respectively.

Conventionally, robots have simply played back programs they were taught. However, owing to feedback technologies using force, position, or various other sensors, robots have come to be able to perform smart operations. In some of these, the capabilities of robots exceed those of human workers. For example, while humans are highly adaptive to various operations, it is difficult for them to maintain a constant force or position for long periods of time.

Generally, humans make decisions about operations according to their experience, and this experience is gained from many instances of trial and error. Now, the trial-and-error learning of AI has become significantly superior to that of humans in terms of both number and speed. As a result, many systems can find operational strategies or answers much faster than humans can.

This special issue features papers on robot hands, path planning, kinematics, and AI. Papers related to robot hands present an actuator using new principles, new movements, and the realization of the precise sense of the human hand. Papers related to path planning present path generation on the basis of CAD data, path generation using image processing, automatic path generation on the basis of environmental information, and the prediction of error and correction. Path generation using VR technology and error compensation using an AI technique are also presented. A paper related to kinematics presents the analysis and evaluation of a new mechanism with the aim of new applications in the field of machining.

In closing, I would like to thank the authors, reviewers, and editors, without whose hard work and earnest cooperation this issue could not have been completed and presented.

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