Robot Sensor Fault Detection is an important part of robotic control and automation systems. Robots depend on sensors such as ultrasonic, infrared, temperature, pressure, encoder, proximity, and camera sensors to understand their surroundings and monitor internal conditions. A faulty sensor can provide incorrect, unstable, or missing data, causing the robot to make unsafe or inaccurate decisions.
Robot sensor fault detection continuously examines sensor readings and compares them with expected values, neighboring sensors, previous measurements, or predefined operating limits. Common faults include sensor disconnection, abnormal values, signal noise, constant readings, intermittent signals, and calibration errors. Controllers can use threshold checking, redundancy, filtering, or intelligent diagnostic algorithms to identify these problems.
When a sensor fault is detected, the robot can take corrective action such as ignoring the faulty reading, switching to a backup sensor, reducing operating speed, stopping a particular movement, or alerting the operator. This improves reliability, safety, and maintenance efficiency. Sensor fault detection is therefore widely used in industrial robots, autonomous vehicles, mobile robots, robotic arms, and other intelligent automation systems.