IMUsensing

IMUsensing refers to the sensing and interpretation of motion data obtained from inertial measurement units (IMUs). An IMU typically combines accelerometers and gyroscopes, and may include magnetometers. It provides measurements of linear acceleration and angular velocity, and, when a magnetometer is present, magnetic field orientation, enabling estimation of device motion and attitude. In practice, IMU sensing underpins tracking of movement in robotics, mobile devices, and wearables.

Raw IMU data are usually processed with sensor fusion algorithms to estimate a coherent state that may include position, velocity, and orientation. Common approaches include Kalman filters, extended or unscented variants, and complementary or Mahony filters. Orientation is often expressed with quaternions or rotation matrices to avoid gimbal lock. Because acceleration data must be integrated to obtain position, IMU sensing is prone to drift over time, underscoring the need for fusion with external references such as GPS, visual odometry, or magnetometer readings.

Calibration is critical to IMUsensing performance. Manufacturers perform factory calibration to determine biases, scale factors, and misalignments, while field calibration addresses changes due to temperature, mounting, and wear. Key performance parameters include accelerometer and gyroscope noise, bias instability, scale factor error, and nonlinearity. Temperature effects and mechanical shocks can degrade accuracy, requiring compensation and filtering.

Applications of IMUsensing span robotics, aerial and ground vehicles, smartphones, and virtual reality systems. Challenges include vibrations, magnetic disturbances, and dynamic motion that challenge fusion algorithms. Ongoing advances focus on improved sensor fusion, adaptive calibration, and integration with other sensing modalities to enhance accuracy and robustness.