  Finding the physical location of a specific network node is a prototypical
task for navigation inside a wireless network. In this paper, we consider in
depth the implications of wireless communication as a measurement input of
gradient-based taxis algorithms. We discuss how gradients can be measured and
determine the errors of this estimation. We then introduce a gradient-based
taxis algorithm as an example of a family of gradient-based, convergent
algorithms and discuss its convergence in the context of network robotics. We
also conduct an exemplary experiment to show how to overcome some of the
specific problems related to network robotics. Finally, we show how to adapt
this framework to more complex objectives.
