Radar Inertial Odometry

Radar Inertial Odometry (RIO) combines radar and inertial measurement unit (IMU) data to estimate the position and orientation of a moving platform, particularly valuable in challenging environments where vision-based systems fail. Current research emphasizes robust algorithms, often employing Kalman filtering or similar techniques, to handle noisy radar measurements and IMU biases, with a focus on improving accuracy and resilience to outliers and sensor degradation through methods like acceleration-based constraints and m-estimators. This technology is crucial for autonomous navigation in various applications, including robotics, autonomous vehicles, and drones, offering a robust alternative to vision-based systems in adverse conditions.