Dragonfly is a visual SLAM technology that uses computer vision to provide the precise location of vehicles, robots, drones, forklifts and any other moving assets equipped with a monocular camera or stereoscopic camera. For vSLAM technologies there are 2 types of accuracy measurements described in the following sections.
1 – Drift and ROC
The “drift” is the location error accumulated over time during the simultaneous navigation and mapping of unknown environments (venues where Dragonfly has not been used before and thus for which there is not yet an existing 3D map like for example, the first time a forklift that makes use of Dragonfly is driven inside a warehouse). The drift can be expressed as a percentage:
- When using stereoscopic cameras – Dragonfly’s drift has been verified to range between 0.6% and 1.3%. This means that if you drive a forklift with Dragonfly installed on board along a 100 meters linear path, at the end Dragonfly will report a location that can be 60 cm to 130 cm inaccurate.
- When using monocular cameras – the drift in itself can be pretty high and must be corrected performing loop-closure (see explanation below). This is why we recommend the usage of monocular cameras only when a pre-mapping is possible. When using monocular camera the measure of accuracy is the radius of confidence (ROC). After a pre-mapping, the ROC is usually 1% of the distance to the closest real-world reference (visual or virtual marker). For instance, in a 15,000 sqm warehouse, the average ROC is about 30 cm.
The drift, and the error for monocular cameras’ systems, are however automatically corrected by Dragonfly each time there is a loop-closure. A loop-closure is triggered each time the camera is moved from an area already mapped to an unknown area and then back to an area already mapped. When this happens Dragonfly corrects the location and the map is also updated. Loop-closures are extremely useful to improve the overall accuracy of the system, and it is strongly recommended to perform frequent loop-closures during the initial mapping, for both monocular and stereo cameras installations. A loop closure is triggered also when an existing map is fused with the a new one (if the map fusion option is active inside the Dragonfly settings).
2 – Linear accuracy
When navigating inside a known environment, therefore when Dragonfly re-locates the device inside a previously created map, the accuracy depends on the precision of the triangulation of known points (features). The radius of confidence, is typically 5-10 cm, and depends on several factors, including:
- The quality of the camera;
- The lightning of the environment;
- The real-world reference;
- The dimension of the map;
- The camera’s calibration.
As an example, imagine a drone navigating inside a hangar that has already been “mapped” before: in this case, the ROC of the drone will be 5-10 cm.