A lot of those (mostly the dead-reckoning, landmarking, path planning) are research topics so you could just search online specifically for PDF format papers for those- and books. There's probably also courses about those (indirectly) at universities.
Not sure about sensor fusion (but I'm betting there it requires boatloads of University courses, none of which are actually directly focused on sensor fusion.) Like Kalman filters...it takes a huge amount of math background to understand how they work, let alone implement = more books needed. Although, they do use these in university group projects, but there are team members with different specialities rather than one person.
For sensors...well there are gyros, accelerometers, rangefinders, etc. It's pretty easy to be intuitive (or just Google) to figure out what each can do and what it can't. It's also fairly easy to figure out the advantages and disadvantages of the different approaches to a sensor (ie. for rangefinding you can use laser, sonar, radar. For gyros you have piezo, ring, wine glass, beam, laser, mechanical). Most of the time you are pretty much limited to one method anyways, since the others are way aerospace-grade expensive.
It's all military, aerospace, and research- so look accordingly. Would they sell these types of books on Amazon? Probably not (although I did find and buy one which was a collection of research papers on flapping wing aerodynamics, many of which I had already downloaded off of the internet. It is SOOOO way over my head and probably always will be, since I am not a mechanical engineer..s o if anyone wants to buy it off me they can! Mint condition!). The problem with robot navigation is that it is not mature- it is research. Even worse, it's an application (which involves many fields) rather than a field. Chances are that any book you find is going to be so technical that it is way over your head(although I am not sure how versed you are). Have you ever heard of a Kalmnan filter? It's used in sensor fusion I believe. It takes a huge amount of math to understand, let alone implement. These are not things you can just gloss over. As such, no one writes books that combine all of this together. As a result of this, it's probably not even referred to as robot navigation (except in research papers and journals).
For example, path planning is an application- an immature, research-level application (with the exception of some application aerospace/military). As such, you probably can't find a book called path planning. The book would probably be some specific generic mathematical/AI method that can be used for as a specific method of path planning. The title is probably a word used in AI to describe algorithms for data collection, interpretation, and optmization.
If you still are looking for a book:
-Don't search for robot navigation, it's so general you'll probably never find anything (particularily on the level you want)
-You'll need to get much more specific
-You'll need much more than one book
-Don't search for a book with robots on the label (robots tends to imply hobbyist on a book a lot of the time. This is not hobbyist stuff)
If I were you, I would not look for books so much as research journals and graduate research papers. Of course, then you will need to get things like advanced statistics and math textbooks to figure the stuff out (but that would probably happen anyways even with a book, unless it was a meter thick.) Normally, I just read those papers to get a conceptual feel. Then I simplify it to something I can actually pull off on my own.
When these things are used in real systems, you have a bunch of engineers each specialized in their particular field. That's how they can use all this stuff. If you are just one person, you can just get creative. Use the sensors you can afford and use more simplistic methods, like weighted averages with guesstimated weightings. Intelligently comparing different sensor readings (using your intuition to come up with the stuff and the field testing it). Like if the readings from two different types of sensors don't "overlap" enough, prioritize one over the other, or reject them altogether. Things like that since you probably don't have the time, money, or ability to learn and implement all of these algorithms and expensive sensor technologies.