Abstract

Unmanned aerial vehicles (UAVs) are being widely exploited for various applications, <i>e.g</i>., traversing to collect data from ground sensors, patrolling to monitor key facilities, moving to aid mobile edge computing. We summarize these UAV applications and formulate a problem, namely the <i>general waypoint-based PoI-visiting problem</i>. Since energy is critical due to the limited onboard storage capacity, we aim at minimizing flight energy consumption. In our problem, we pay special attention to the energy consumption for turning and switching operations on flight planning, which are usually ignored in the literature but play an important role in practical UAV flights according to our real-world measurement experiments. We propose specially designed graph parts to model the turning and switching cost and thus transfer the problem into a classic graph problem, <i>i.e</i>., general traveling salesman problem, which can be efficiently solved. Theoretical analysis shows that such problem transformation has the graph redefinition approximation ratio upper bound, <inline-formula><tex-math notation="LaTeX">$max\lbrace \Theta /\delta ,2\rbrace$</tex-math></inline-formula>, where <inline-formula><tex-math notation="LaTeX">$\Theta$</tex-math></inline-formula> is related to the designed graph parts and <inline-formula><tex-math notation="LaTeX">$\delta$</tex-math></inline-formula> is a constant. Finally, we evaluate our proposed algorithm by simulations. The results show that it costs less than 107&#x0025; of the optimal minimum energy consumption for small scale problems and costs only 50&#x0025; as much energy as a naive algorithm for large scale problems.

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