Tag Archives: UAV Network

Paper accepted in Transactions on Vehicular Technology

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Our paper entitled “Dynamic Multi-UAV Path Planning for Multi-Target Search and Connectivity” is accepted for publication in IEEE TVT.

In this work, we propose and analyze multi-drone path planners for multi-target search and connectivity. The goal of the unmanned aerial vehicle (UAV) mission is to search an unknown area to detect, connect and monitor multiple randomly distributed targets to the ground control station (GCS) while maintaining the connectivity of the UAVs to GCS. To this end, we propose to use two types of UAVs: search and relay. The search drones scan the area via onboard sensors, whereas relay UAVs provide connectivity. We propose three different responses to target detection with increasing adaptability: (i) follow pre-planned paths and inform GCS when possible, (ii) follow pre-planned paths and inject new UAVs to monitor the detected targets, (iii) assign a search UAV to monitor target, and re-plan remaining UAV paths. Furthermore, we implement multi-objective optimization-based planners for single-type UAVs, where the paths are optimized in terms of total coverage time and percentage connectivity.

Paper accepted in Ad Hoc Networks Journal

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Our paper entitled “Multi-objective path planning for multi-UAV connectivity and area coverage” is accepted for publication in Ad Hoc Networks journal.

In this paper, we propose a multi-drone path planner that jointly optimizes area coverage time and connectivity among the drones. We propose a novel connectivity metric that includes not only percentage connectivity of the drones to GCS, but also the maximum duration of consecutive time that the drones are disconnected from the GCS. To solve this optimization formulation, we propose a multi-objective evolutionary algorithm with novel operations. We use our solver to test single, two and many objective path planning problems and compare our Pareto-optimal solutions to benchmark weighted-sum based solutions.

Paper accepted in INFOCOM Workshop

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Our paper entitled “Network Analysis of Connectivity Optimized Multi-UAV Path Planners” is accepted for publication in 17th IEEE INFOCOM Workshop on Networked Robotics and Communication Systems (ex WISARN).

In this work, we analyze the network performance of several connectivity -optimized multi-UAV path planners. We analyze jointly optimized as well as relay assisted UAV networks. Our results show that topologically connected multi-UAV paths do not necessarily lead to acceptable network performance in terms of packet delivery rates and throughput. Mobile relay assisted scenarios perform as well as static relay scenarios with less than half the number of relay nodes. Jointly optimized schemes perform well with low number of UAVs when the transmission ranges are high or the number of nodes is low, where hub nodes are less likely to occur.

Paper accepted at IEEE WCNC 2024

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Our paper entitled “Priority-based Dynamic Multi-UAV Positioning for Multi-Target Search and Connectivity” is accepted for publication in IEEE WCNC 2024.

In this work, we propose an event-driven algorithm that integrates a novel connectivity-based prioritization of targets into dynamic positioning and path planning for multi-UAV systems in search and rescue (SAR) missions. Two distinct groups of UAVs are deployed. While search UAVs sense the area of interest as fast as possible, relay UAVs provide connectivity to search UAVs as well as targets depending on their priority level.

Paper accepted at ACM DiVANET 2023

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Our paper entitled “Maintaining connectivity for multi-UAV multi-target search using reinforcement learning” is accepted for publication in ACM DiVANET 2023.

In this paper, we propose a dynamic path planner that uses a multi-agent reinforcement learning (MARL) model with novel reward functions for multi-drone search and rescue (SAR) missions. The training procedure of the agents includes a convolutional neural network (CNN) that uses images which represent trajectory histories and connectivity states of each environment entity such as drones, targets, BS. Agents take actions and get feedback from the environment until the mission is completed. The model is trained with multiple missions with randomized target locations.

Paper accepted at Ad hoc Networks Journal

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Paper entitled “Joint or Decoupled Optimization: Multi-UAV Path Planning for Search and Rescue” is accepted for publication in Ad Hoc Networks Journal within “Drone Network for Post-Earthquake Search and Rescue” project.

Article focuses on path planning of drone teams deployed for search and rescue missions. We compare selected joint and decoupled multi-drone path planning approaches
from mission and connectivity perspectives. We illustrate the trade-off between performance metrics from both viewpoints and show that depending on the available resources (e.g., number of drones) and the search area most suitable planner can change. We also propose a hybrid planner which uses a connectivity-wise better pre-mission plan.

Paper accepted in Ad Hoc Networks Journal

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Our paper entitled “Positioning aerial relays to maintain connectivity during drone team missions” is accepted for publication in Ad Hoc Networks Journal.

In this work, we deploy UAVs as relays to support mission-oriented UAV networks in order to decouple the mission and communication tasks. We propose a modular relay positioning and trajectory planning algorithm that guarantees connectivity of the UAV mission team with minimum number of relays and feasible trajectories, where the cost, network structure and setup can be changed, allowing its use for different types of missions, without relying on infrastructure. We propose different approaches to relay position decisions and compare the proposed schemes with an ideal scheme and a Voronoi-based benchmark scheme. Our results show that different solutions are applicable for achieving fewer number of relay nodes, higher utilization or lower number of hops between the nodes.

Open positions

Featured

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Interested students can contact me about taking part in projects with topics on networked autonomous systems, multi-drone networks, and cooperative networking. Expertise in one of the following fields is expected: wireless networks, multi-robot coordination, UAV swarming, testbed design, ROS.

To apply: prepare a single PDF file that contains a letter of interest that indicates which position you are applying for and outlines why you are suitable for it; current CV with list of publications; diplomas, transcripts, and contact details of two references. Please send your application file to eyanmaz@alumni.cmu.edu. Scholarship and/or financial aid can be provided following Ozyegin University guidelines. For more info, visit https://www.ozyegin.edu.tr/en/graduate-school-engineering-and-science/financial-aid


Paper accepted in IEEE Networking Letters

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Paper entitled “Dynamic Relay Selection and Positioning for Cooperative UAV Networks” is accepted for publication in IEEE Networking Letters.

This letter analyzes resource reservation for networking purposes in drone teams deployed for search and rescue missions. Building on a well-known static relay positioning technique that minimizes the number of drones, we propose a positioning and trajectory planning algorithm for relay nodes to provide connectivity to drones that are on a search and rescue mission.

Paper accepted in IEEE Transactions on Mobile Computing

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Our paper entitled “Take the Field from your Smartphone: Leveraging UAVs for Event Filming” is accepted for publication in IEEE TMC.

This paper formulates an event coverage problem, namely, Sport Event Filming, with Connectivity Constraints, in which  a team of Unmanned Aerial Vehicles (UAV) fly over a limited field in order to track the movements of an object (e.g., of the ball) and to deliver a video stream of the events (e.g., ball passes, goals) to the spectators meeting certain timeliness and video quality criteria. In addition to a mathematical model that determines the sequence of optimum movements for the UAVs, we also provide dynamic, artificial potential function based, distributed UAV movement schemes to optimize networking performance.