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Robotics & Automation13 September 2026 · 1 min read

Robots Are Learning to Feel — Why Touch Is the Next Front in Automation

A global race to build tactile data for robots is targeting the one job machines still cannot do: handle the real world the way human hands do.

Robots Are Learning to Feel — Why Touch Is the Next Front in Automation
AIAI Summary

Robots still fail at everyday physical tasks — packing mixed items, plugging in connectors, handling delicate parts — because they cannot feel what they are touching. According to an IEEE Spectrum report, academic labs and startups are now racing to build the missing ingredient: large, high-quality tactile datasets and the techniques to use them, following the path that vision-language-action (VLA) models opened for camera-driven robot control. For Malaysian readers of AI news Malaysia trusts for decisions, the signal is clear: the next automation wave will reach the dexterity-heavy work in Penang's electronics plants, glove factories, and e-commerce warehouses that robots have never been able to touch — pun intended. The technology is early. The practical move this quarter is not buying, but preparing your processes and data.

AI Summary

Robots still fail at everyday physical tasks — packing mixed items, plugging in connectors, handling delicate parts — because they cannot feel what they are touching. According to an IEEE Spectrum report, academic labs and startups are now racing to build the missing ingredient: large, high-quality tactile datasets and the techniques to use them, following the path that vision-language-action (VLA) models opened for camera-driven robot control. For Malaysian readers of AI news Malaysia trusts for decisions, the signal is clear: the next automation wave will reach the dexterity-heavy work in Penang's electronics plants, glove factories, and e-commerce warehouses that robots have never been able to touch — pun intended. The technology is early. The practical move this quarter is not buying, but preparing your processes and data.

Key Takeaways

  • Dexterous manipulation — adjusting grip on irregular, fragile, or variable objects — is the single biggest barrier keeping robots out of everyday tasks, per the IEEE Spectrum report.
  • The bottleneck is not touch sensors

Sources & References

AIBlog summarises and analyses published information. We do not reproduce full source text. Analysis is editorial and not financial or legal advice.

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