Proprioception

Signals from the robot's own body#

Proprioceptive sensors report quantities generated within the robot rather than a direct observation of distant surroundings. A joint encoder measures a joint position or motion, while an inertial measurement unit measures angular velocity and specific force. Motor-current, torque, and contact signals may also contribute information about the body's state.

The sensor readings are not the same as a complete state estimate. Agrawal and colleagues combine preintegrated inertial measurements, forward kinematics, and contact detections in a factor graph to estimate a legged robot's base and joint states. The robot model and estimator turn incomplete, noisy measurements into quantities a controller can use.

Proprioception and exteroception answer different questions#

Exteroceptive sensors such as cameras and lidar observe the environment. Proprioception can reveal that a foot has loaded or slipped, but it does not provide a distant terrain map before contact. Conversely, a depth image can show an obstacle without directly measuring the torque at a knee.

In reported quadruped experiments, Miki and colleagues combine proprioceptive and exteroceptive inputs for terrain-aware locomotion. Their result is evidence for that trained controller and set of tests. It does not make either sensing mode universally reliable.

Internal sensing still has blind spots#

Inertial integration drifts, encoders can contain offsets, and leg odometry can be wrong when a presumed stationary foot slips. Contact state itself may need to be inferred. Proprioception also cannot identify many external hazards until they affect the body.

Sensor fusion can combine internal and external observations, but its output depends on calibration, timing, noise models, and correct contact assumptions. A robot that continues moving plausibly is not proof that its estimated position or terrain model is correct.