Summary: Abstract--Unmanned aerial vehicles (UAVs) represent an impor-
tant class of networked robotic applications that must be both highly de-
pendable and autonomous. This paper addresses sensor selection and
placement problems for distributed failure diagnosis in such networks
where multiple vehicles must agree on the fault status of another UAV.
An integer linear programming (ILP) approach is proposed to solve
these problems. The ILP models of interest are developed and solved
using two different solvers. Experimental results indicate that the pro-
posed models are tractable for medium-sized topologies.
Index Terms--UAV networks, fault diagnosis, ad hoc sensor net-
works, distributed systems.
Unmanned aerial vehicles (UAVs) represent an important class of
robotic applications for distributed sensing and control. A collection of
vehicles must perform a shared task while coordinating the required in-
ter-vehicle actions using wireless communication. Examples include
remote sensing, surveillance and patrol, and data collection over areas
dangerous to human intervention. Such UAV networks have significant
cost constraints. However, they must be both highly dependable and
largely autonomous, requiring only high-level guidance from ground