> I'm an EE, I have worked with things like sensor fusion professionally. In short sensor fusion depends on what sensors you have and how you combine them, especially if two sensors' outputs tend to disagree - which one is wrong and to what extent, and how a piece of noise gets reflected in each sensors' outputs, to avoid double counting errors and coming up with unjustifyably confident results.

> This field is extremely complex, it's often better to pick a sensor and stick with it rather than trying to figure out how to piece together data from very dissimilar sources.

Whether sensor fusion makes sense is a highly domain specific question. Guidance like "pick a sensor and stick with it" might have been correct for the projects you've worked on, but there's no reason to think this translates well to other domains.

For what it's worth, sensor fusion is extremely common in SLAM type applications.