Speed and Separation Monitoring in Practice

Visualization of Sensory's SR-1 SSM Safety Zone shows a 3D model highlighting safe interaction boundaries between a robotic arm and a human operator, utilizing red and green wireframes to indicate proximity and safety limits.

Speed and separation monitoring (SSM) sounds simple: keep enough distance between a person and a hazard. In real cells, it gets messy fast. You need stop times, approach speeds, detection performance, and a clear plan for how the robot behaves when someone enters a zone.

Most SSM failures don’t come from bad intent. They come from missing inputs:

• Stop time measured once, not validated over time

• Assumed approach speeds that don’t match real movement

• Zones that don’t reflect the true workspace

• Inconsistent definitions of reduced speed vs stop behavior

• Poor documentation for validation and audits

SR-1 supports SSM by providing a live 3D understanding of the workspace and a consistent way to trigger safe behavior. Your risk assessment defines what “safe” means stop, reduced speed, or a combination, and SR-1 helps you execute that behavior based on real-world conditions.

What “good SSM” looks like:

• You measure stop time under realistic conditions

• You document assumptions (speeds, paths, detection coverage)

• You validate the safety function and monitor health over time

• You define what happens at each boundary: warn, slow, stop

• You keep the logic understandable for integrators and auditors

  
  

SSM can improve productivity, but only when the design matches reality.

Request a demo or download our SSM intake checklist to benchmark your current setup.