Summary of A Gripping Problem

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Robots contribute precise, efficient work to many industries, and their use continues to expand, fueled by new technology. Today’s robots build and pack products with amazing efficiency, but their ability to grasp and manipulate objects remains limited. Researchers address these critical challenges through repetitive machine learning, advanced software and soft, human-like hand designs. Those curious about both the possibilities and limitations of today’s industrial robots will be engaged by this overview of new developments.

In this summary, you will learn

  • Why robotics researchers struggle to teach robots how to grasp,
  • What methodology scientists use to attack the gripping problem, and
  • What limitations robots currently have in identifying and manipulating objects.
 

About the Author

Richard Hodson writes for Nature Outlook supplements. He gained an MA in science journalism from City University London, and studied biomedical science at King’s College London.

 

Summary

Scientists have developed impressive functionality for robots over the past 50 years, but grasping and dexterity remain critical challenges.

Although robots function successfully in many industries today, the real world is not an assembly line, where actions are continuously repeated. Today’s robots are learning to interact intuitively with a variety of objects. Engineers and industry leaders predict these new capabilities will have a profound impact on society and commerce.

Researchers use machine learning and improved software  to address the gripping...


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