Sensor-Only Tracking
Sensor-Only Tracking is a computer vision and robotics technique that estimates the position and orientation (pose) of objects or cameras using only data from onboard sensors, such as inertial measurement units (IMUs), without relying on external references like GPS or visual markers. It is commonly used in applications like augmented reality (AR), virtual reality (VR), and autonomous navigation where real-time, self-contained localization is critical. This approach leverages sensor fusion algorithms to combine data from accelerometers, gyroscopes, and sometimes magnetometers to track motion in 3D space.
Developers should learn Sensor-Only Tracking for applications requiring robust, low-latency pose estimation in environments where external signals are unavailable or unreliable, such as indoor navigation, drone control, or AR/VR headsets. It is essential in scenarios where privacy, independence from infrastructure, or operation in GPS-denied areas (e.g., underground or indoors) is a priority, providing a fallback or primary tracking method in hybrid systems.