Sensor selection and placement for failure diagnosis in networked aerial robots

Abstract

Unmanned aerial vehicles (UAVs) represent an important class of networked robotic applications that must be both highly dependable 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 proposed models are tractable for medium-sized topologies