Abstract
This paper proposes a framework for the wireless sensor data acquisition using a team of Unmanned Aerial Vehicles (UAVs). Scattered over a terrain, the sensors detect information about their surroundings and can transmit this information wirelessly over a short range. With no access to a terrestrial or satellite communication network to relay the information to, UAVs are used to visit the sensors and collect the data. The proposed framework uses an iterative k-means algorithm to group the sensors into clusters and to identify Download Points (DPs) where the UAVs hover to download the data. A Single-Source–Shortest-Path algorithm (SSSP) is used to compute optimal paths between every pair of DPs with a constraint to reduce the number of turns. A genetic algorithm supplemented with a 2-opt local search heuristic is used to solve the multi-travelling salesperson problem and to find optimized tours for each UAVs. Finally, a collision avoidance strategy is implemented to guarantee collision-free trajectories. Concerned with the overall runtime of the framework, the SSSP algorithm is implemented in parallel on a graphics processing unit. The proposed framework is tested in simulation using three UAVs and realistic 3D maps with up to 100 sensors and runs in just 20.7 s, a 33.3× speed-up compared to a sequential execution on CPU. The results show that the proposed method is efficient at calculating optimized trajectories for the UAVs for data acquisition from wireless sensors. The results also show the significant advantage of the parallel implementation on GPU.
Highlights
Wireless Sensor Networks (WSNs) are composed of a large number of sensor nodes deployed to monitor physical phenomena
The proposed framework uses an iterative method based on the k-means clustering algorithm to group the sensors into clusters and identify the location of Download Points (DPs), locations where the Unmanned Aerial Vehicles (UAVs) hover to download the data from the sensors that are part of the cluster
This paper presented a framework for the path planning of a team of UAVs tasked to download data from wireless sensors scattered over a 3D environment
Summary
Wireless Sensor Networks (WSNs) are composed of a large number of sensor nodes deployed to monitor physical phenomena. WSNs can be used to monitor a terrain for ground troop or vehicle movements In these applications, sensor nodes are low-power devices often using the IEEE 802.11af and 802.15 protocols and capable of communicating over a short range [2]. In the case of a remote WSNs such as in military theater or in emergency situations where the WSNs are rapidly deployed in the environment, there is usually no infrastructure in place to accept the gateways. Compared to unmanned ground vehicles, UAVs can cover more terrain in a shorter period of time They can be used in a rugged environment that would be difficult or impossible to reach by land. To accelerate the data collection, a team of collaborating UAVs can be used
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