Optimizing Communication and Computation for Multi-UAV Information Gathering Applications

Abstract

Mobile agent networks, such as multi-UAV systems, are constrained by limited resources. In particular, limited energy affects system performance directly, such as system lifetime. It has been demonstrated in the wireless sensor network literature that the communication energy consumption dominates the computational and the sensing energy consumption. Hence, the lifetime of the multi-UAV systems can be extended significantly by optimizing the amount of communication data, at the expense of increasing computational cost. In this work, we aim at attaining an optimal trade-off between the communication and the computational energy. Specifically, we propose a mixed-integer optimization formulation for a multi-hop hierarchical clustering-based self-organizing UAV network incorporating data aggregation, to obtain an energy-efficient information routing scheme. The proposed framework is tested on two applications, namely target tracking and area mapping. Based on simulation results, our method can significantly save energy compared to a baseline strategy, where there is no data aggregation and clustering scheme. I. INTRODUCTIONInexpensive mobile agents, such as unmanned aerial vehicles (UAVs), are useful for several remote monitoring applications such as agriculture [1], geology [2], ecology [3] and forestry [4]. The viability of UAVs for scientific and non-military applications are due to reduced cost of the UAVs, low sensor cost and ease in handling. Typically, these applications are of large scale and the mission time can be shortened by introducing multiple UAVs.Central to these applications is the necessity to have a human-in-the-loop (HITL) capability that increases situational awareness and operator autonomy to modify missions dynamically. For HITL, UAVs have to gather and disseminate information periodically to the operator who may be located at a distant (base station) from the operational arena. Typical information required at the base station is aerial footage [5], which is a communication intensive operation consuming considerable energy. Unfortunately, low cost UAVs have limited flight time due to battery/fuel capacity. Hence, there is a need to find different mechanisms by which flight time endurance can be increased. One way is to use gliders that take advantage of the updrafts to soar for long endurance [6]. However, during soaring it is very difficult to maintain a good resolution of the terrain due to varying UAV height for mapping or surveillance applications. Instead, we propose to optimize the energy consumed by various units in a given aircraft to increase the flight time and hence the UAV team mission time.For many applications [1], [4], it is necessary that a UAV must fly at a constant speed and maintain a prescribed height. Under these conditions, the major energy consumption units are propulsion, sensing, computation and communication. On average, the power consumed during flight is approximately constant. The sensing and the computational units also consume constant power. However, the energy e...

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