Drift in Augmented Reality, causes of Drift and how to reduce Drift in AR Apps.

Written with the assistance of ChatGPT and reviewed by the author.

Augmented Reality (AR) technology has become an increasingly popular tool for enhancing the way we interact with our physical environment. AR allows us to overlay digital information on the real world, creating a more immersive and interactive experience. However, one of the challenges of AR technology is drift. In this article, we will examine what drift is, the causes of drift, and ways to reduce drift in AR applications.

What is Drift in AR?

Drift refers to the discrepancy between the position and orientation of the digital objects in the AR world and their actual position in the physical world. When drift occurs, the digital objects in the AR world may appear to move or drift away from their intended position, even when the device is stationary. This can be confusing and disorienting for users, making it difficult to effectively use AR applications.

Example of spatial drift -”Different Reality”

Causes of Drift in AR

Drift in AR is caused by a combination of factors, including the limitations of the device’s sensors and the algorithms used to track the position and orientation of the device in the real world. The most common causes of drift include:

1. Sensor Noise: The sensors used in AR devices, such as accelerometers and gyroscopes, are susceptible to measurement errors caused by sensor noise. This noise can accumulate over time, causing the digital objects in the AR world to appear to drift.
2. Tracking Loss: AR devices rely on visual markers or other features in the environment to track their position and orientation. If these markers or features are not visible, tracking may be lost, causing the digital objects in the AR world to appear to drift.
3. Algorithm Limitations: AR algorithms are designed to estimate the position and orientation of the device based on the data from the sensors and the visual markers in the environment. However, these algorithms are limited by their accuracy and the quality of the data they receive.
4. Interference from External Factors: External factors, such as ambient light, electromagnetic interference, and other sources of noise, can interfere with the AR device’s sensors and algorithms, causing drift in the AR world.
5. User Movement: User movement can also cause drift in AR applications, especially if the AR device is not able to track the user’s movements accurately.

Reducing Drift in AR Applications

To reduce drift in AR applications, developers must address the underlying causes of drift and use techniques to mitigate the impact of these causes. Some of the most effective ways to reduce drift in AR include:

1. Improving Sensor Accuracy: By using high-quality sensors and reducing the amount of noise in the sensor data, developers can improve the accuracy of the AR device’s tracking.
2. Enhancing Tracking: Developers can use advanced tracking algorithms, such as SLAM (Simultaneous Localization and Mapping), to improve the robustness of the AR device’s tracking even in challenging environments.
3. Incorporating Context: AR algorithms can be designed to incorporate contextual information, such as the user’s movements, the environment, and other factors, to improve the accuracy of the AR device’s tracking.
4. Calibration: AR devices can be calibrated to improve the accuracy of the AR device’s tracking. Calibration can be performed using a combination of hardware and software techniques to reduce the impact of drift.
5. Scene optimization: AR scenes can be large most of the time and rendering of that scene itself impact the drift during an AR session, hence scene optimization such as Static batching, pre-baking of scene lights, reducing object search calls, lazy loading, and string game object in the cache when possible is required to optimize AR scenes.
6. Pose Correction: frictionless relocalization at regular intervals in large-scale AR scenes can mitigate the drift that occurred in the AR session. Relocalization can be done using visual markers, point clouds, or wireless location transfer techniques.

Pose correction at regular intervals

Conclusion

AR technology has the potential to revolutionize the way we interact with our physical environment. However, drift remains one of the biggest challenges in AR technology. By understanding the causes of drift and using techniques to reduce drift, developers can create more accurate and reliable AR applications that deliver an immersive and engaging experience for users.

At ARway we are constantly working on reducing drift in our Applications and SDKs which mainly target large-scale indoor navigation and AR experiences, we are solving this problem by improving the underlying tech and improving user experience in drift detection, and prompting users to do frictionless re-localization when required.