What vision navigation can mean
Vision navigation is a broad label. A robot mower may use cameras to identify lawn edges, recognize obstacles, estimate its own movement, build a map or support another positioning technology. Two products can both say “vision” while using the cameras for very different jobs.
Vision as primary navigation
Some mowers navigate primarily from camera perception and local mapping. This can avoid the need for an RTK antenna and may work well where the yard has enough visual structure. Performance depends heavily on the quality of the cameras and the software interpreting the scene.
Vision as a supporting layer
Other products use RTK or LiDAR for primary localization and add cameras for obstacle recognition or fallback positioning. This hybrid approach can be valuable because the system is not asking one sensor to solve every problem.
Practical limitations
Lighting changes, shadows, glare, darkness, lens contamination and ambiguous boundaries can affect camera perception. A well-designed mower anticipates these conditions with additional sensors or conservative behaviour rather than assuming the camera is always perfect.
What buyers should ask
- Is vision the main localization method or only obstacle detection?
- Does the mower need visible lawn edges?
- How does it work at dusk or under heavy shade?
- What other sensors support the cameras?
- Can the user define no-go zones and virtual boundaries independently of what the camera sees?