Editorial Feature

Using Automated Robots to Conduct Fatigue Analysis

ImageForArticle_341_1580900498604269.png

Image Credit: LightField Studios/Shutterstock.com

In 2017, research was published that had devised a method that allows robots to reliably read signs of fatigue in human beings to adapt their behavior whilst conducting human-robot co-manipulation tasks.

The Rise of Hybrid Decision-Making

For decades there has been a fear of the takeover of artificial intelligence (AI), leaving humans redundant, with robotics replacing humans in jobs in all sectors. However, experts believe a more realistic view of the future is one where humans and robots work alongside each other, where the best of both systems, of AI and the human brain, are harnessed through collaborative working. This development is known as hybrid decision-making and it is predicted to yield better results than either robotics or humans working alone. Therefore, much research has been underway in recent years with the aim of developing systems that support robots and humans working together.

Fatigue Analysis to Improve Collaborative Working

The team of scientists based in Italy developed a system that allows humans and robots to work together in a way that supports joint work on tasks that take a long time to complete. The system that the Italian team established was based on the dynamical movement primitives, locally weighted regression and adaptive frequency oscillators.

In a collaborative task, the robot begins by copying the human’s actions, using feedback to imitate human motor behavior. The robot simultaneously develops the motor skills required for the task.

The researchers programmed the robots to detect signs of fatigue in the human worker and set a predetermined level of fatigue to trigger a switch in robot behavior. To register human fatigue the robot monitors muscle activity using electromyography which delivers data to the robot reporting on reliable markers of fatigue.

Once the human is recognized as being tired, the robot uses the skills it learned from the human to take over the physically demanding part of the task, allowing the human to rest. Rather than conducting the strenuous part of the job, the human instead supervises the high-level interaction behavior, as well as collaborating with the robot on parts of the task that require both of them to complete.

This allows work to continue at a steady pace, even when the human worker becomes fatigued. The idea is that production could benefit from combining the advantages of a human and a robot workforce.

The system that the team developed was successful in real-world co-manipulation tasks, where the situation was impacted by both environmental constraints and dynamic uncertainties.

The Impact of Fatigue Analysis

What the Italian team achieved was a reliable system that supports collaboration between robots and humans. This kind of work is expected to have a significant impact on industry and the economy. It also reduces the fear around the adoption of robotics, demonstrating that collaboration, not replacement, is key. Industries benefit from this kind of work by reducing the physical strain on humans, supporting efficient production management, and allowing for different kinds of jobs to be conducted with ease and speed.

It also allows companies to become more competitive, as well as opening the door to new potential business models focused on providing new goods and services. It also facilitates increased efficiency and flexibility. Experts in economic processes believe that the increased productivity that collaborative work could bring would even improve the Gross Domestic Product of the country.

Sources and Further Reading

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Sarah Moore

Written by

Sarah Moore

After studying Psychology and then Neuroscience, Sarah quickly found her enjoyment for researching and writing research papers; turning to a passion to connect ideas with people through writing.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Moore, Sarah. (2020, February 05). Using Automated Robots to Conduct Fatigue Analysis. AZoRobotics. Retrieved on October 05, 2024 from https://www.azorobotics.com/Article.aspx?ArticleID=341.

  • MLA

    Moore, Sarah. "Using Automated Robots to Conduct Fatigue Analysis". AZoRobotics. 05 October 2024. <https://www.azorobotics.com/Article.aspx?ArticleID=341>.

  • Chicago

    Moore, Sarah. "Using Automated Robots to Conduct Fatigue Analysis". AZoRobotics. https://www.azorobotics.com/Article.aspx?ArticleID=341. (accessed October 05, 2024).

  • Harvard

    Moore, Sarah. 2020. Using Automated Robots to Conduct Fatigue Analysis. AZoRobotics, viewed 05 October 2024, https://www.azorobotics.com/Article.aspx?ArticleID=341.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this article?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.