AIToday
RoboticsRobotics & Automation NewsPublished: Oct 20, 2026, 06:01 JST

ASTM drafts WK100792 to test robots under degraded optics

ASTM drafts WK100792 to test robots under degraded optics

3 Key Points

  1. What happened

    ASTM International's robotics committee (F45) is developing proposed method WK100792, which measures how degraded optical information affects a manipulator's task performance.

  2. Why it matters

    The standard could help developers identify system limitations before real-world deployment, including edge cases hard to capture in training data.

WHO IT HITSRobot manufacturers, perception and machine-learning developers, system integrators, end users, and testing laboratories would use the method to assess performance under controlled degradation before deployment.

Not sure about something? Ask the AI

Questions and answers are published on this page.

Summaries like this, in your inbox every morning.

Context & Analysis

The proposed standard comes as robots increasingly move from controlled settings into warehouses and farms, where optical sensors face unpredictable conditions. ASTM International member Aarati Noronha notes that tasks a robot performs reliably under ideal conditions become much harder in the real world. Stressors such as changing light, reflective materials, interference, and high temperatures can degrade the information from cameras, acting as a distractor for downstream machine-learning models. The proposed method would provide a repeatable way to measure performance under controlled degradation, which Noronha says could help identify system limitations before real-world deployment. The standard is also positioned to support United Nations Sustainable Development Goal #8 on decent work and economic growth.

FAQ
What does the proposed standard measure?
It measures the extent to which degradation in optical information affects a robot's task performance, using a repeatable method under controlled degradation.
Who would use this standard?
Robot manufacturers, perception and machine-learning developers, system integrators, end users, and testing laboratories, according to ASTM International member Aarati Noronha.
Why is optical degradation a problem for robots?
Real-world conditions like changing light, reflective materials, interference, and high temperatures can degrade sensor input, requiring compensation that adds system latency, power use, and compute complexity.
Robotics & Automation NewsRead Original Article

AI news that matters for your work, delivered every morning.

Pick your industry and the AI tools you use, and get news related to your work every day.

Free · 30 seconds with Google · unsubscribe anytimeWhat is AIToday? →

Ask AI

Ask AI anything about this article. The AI reads this article, earlier AIToday articles, and Wikipedia, and cites its sources. Q&As are published on this page for other readers too.

Questions and answers are published on this page.

Related Articles

Next articleMorgan Stanley: 91.7% of Nvidia 2027 revenue tied to AI build-out