What VSLAM means
VSLAM is Visual Simultaneous Localization and Mapping. Instead of relying mainly on a laser scanner, the robot uses camera images to identify visual features and track how those features move from frame to frame.
How a mower uses visual features
Edges, textures, corners and recognizable objects can help software estimate motion and orientation. Over time, the mower can build or reference a map and use that visual information to localize itself. Stereo or multi-camera arrangements can also provide depth cues.
Strengths
Cameras can capture rich environmental information and can support both localization and object recognition. The same perception stack may help a mower understand boundaries, identify obstacles and supplement satellite positioning.
Limitations
Visual systems are sensitive to the quality of the scene. Strong glare, darkness, dirty lenses, low-texture areas or repetitive patterns may make feature tracking harder. Manufacturers often combine VSLAM with inertial sensors, wheel odometry, RTK or other ranging sensors to improve robustness.
Buyer takeaway
“Vision” and “VSLAM” should not be treated as synonyms for obstacle avoidance. A mower may use cameras for localization, object detection, boundary recognition or all three. Check what the cameras actually do in that specific model.