Expected Coverage of Random Walk Mobility Algorithm
This work addresses the need for theoretical analysis of mobility algorithms in UAV-based area exploration, but it is incremental as it builds on existing random walk methods.
The paper tackles the problem of analyzing the expected coverage of a symmetric random walk mobility algorithm for UAVs exploring areas, and it provides an analytical solution by proving event dependencies and developing Markov models, with results compared to prior work and simulations.
Unmanned aerial vehicles (UAVs) have been increasingly used for exploring areas. Many mobility algorithms were designed to achieve a fast coverage of a given area. We focus on analysing the expected coverage of the symmetric random walk mobility algorithm with independent mobility. Therefore we proof the dependence of certain events and develop Markov models, in order to provide an analytical solution for the expected coverage. The analytic solution is afterwards compared to those of another work and to simulation results.