Robot Perception Pipeline

Robot Perception Pipeline
The processing stages by which a robot interprets sensory observations for planning and control.
Area	Physical AI and robotics
Applications	Research, engineering and systems operation

Robot Perception Pipeline the processing stages by which a robot interprets sensory observations for planning and control.

Inputs and transformations

A perception pipeline may begin with camera, lidar, inertial, force or position signals. Processing can include calibration, filtering, synchronization, object recognition, tracking, localization and uncertainty estimation.

Sensor limitations

Occlusion, reflections, noise, changing light and sensor failures can reduce confidence. Combining multiple sensors may help but also introduces calibration and timing problems.

System integration

Perception outputs must use coordinate frames and timestamps understood by a planner or controller. An otherwise accurate detector may be ineffective if data are stale or not aligned with the robot configuration.

Testing

Performance should be tested under the intended environment and with known failure cases. A perception component is not equivalent to a complete autonomous or safety-certified system.

See also

• Computer Vision
• Sensor Fusion
• Physical AI Benchmarking

Further reading

• AI Risk Management Framework (AI RMF 1.0) — NIST
• RT-2: New model translates vision and language into action — Google DeepMind