u/Few_Block_7246

I'm thinking a lot about safety frameworks for robotics, and I'm hitting a wall. Safety is never one-size-fits-all. it's tied to the specific robot form and the exact task. To build a reliable safety guard system, it needs grounded perspective from actual deployments. I’d love to hear your war stories and experiences!

The pucker moment in your deployment?
If an industrial arm hits a thermal limit while holding a payload, what’s the least-bad move? Should it lock in place, or try to safely set the load down before cutting power?

What metrics tell you things are going south?
At the moment a safety system intervenes, what context do you need to see? (Sensor thresholds, spatial boundaries, force/torque limits, SOPs, etc.)

Situations where you use hard constraints?
Besides fk, joint or speed limitations, what other rules must be defined in practice?

I'm trying to design a safety framework flexible across industries—assistant robots, rescue automation, manufacturing, or AVs. Any hard-earned lessons would be helpful!

I've been thinking a lot about safety frameworks for robotics lately, and I'm hitting a wall.

The biggest challenge I'm running into is that safety is never one-size-fits-all

it's extremely tied to the specific robot form factor and the exact task it's performing. To build a more transparent and reliable safety reasoning system, I really need more grounded perspective from actual deployments.

I'm particularly interested in how experienced people in the field define and handle safety in practice. Would love to hear from engineers, roboticists, or operators working on real systems:

1. Most error-prone or high-stress task in your use case What’s the specific task that tends to go wrong or causes the most stress? (e.g., a surgical robot arm during a delicate procedure, a mobile robot navigating a crowded warehouse, or an industrial arm handling fragile/expensive parts). When things start going sideways, what exact decision or action do you want the robot to take?
2. What counts as your ground truth for safety? At the moment a safety system has to intervene, what data or context do you need to see to truly understand why the robot attempted that move? (specific sensor thresholds, spatial boundaries, force/torque limits, SOPs, etc.)
3. Edge cases that should never be left to the AI model Are there certain types of physical surprises, rare failures, or environmental noise that you believe must be handled by a hard-coded/external safety layer rather than probabilistic models? What are the scariest or most unpredictable situations you've encountered or worry about?

I'm trying to design a safety framework that can be flexible across different robots and industries, so any real-world examples (good or bad) would be incredibly helpful

especially from assistant robot, rescue automation, manufacturing, autonomous vehicles, or any other deployed systems.

Thanks in advance! Really appreciate any war stories or hard-earned lessons from the field.