Özsoyeller, Deniz
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Deniz Özsoyeller
Job Title
Dr.Öğr.Üyesi
Email Address
Main Affiliation
01.01.09.07. Yazılım Mühendisliği Bölümü
Status
Current Staff
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ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
1NO POVERTY
0
Research Products
2ZERO HUNGER
0
Research Products
3GOOD HEALTH AND WELL-BEING
0
Research Products
4QUALITY EDUCATION
0
Research Products
5GENDER EQUALITY
0
Research Products
6CLEAN WATER AND SANITATION
0
Research Products
7AFFORDABLE AND CLEAN ENERGY
0
Research Products
8DECENT WORK AND ECONOMIC GROWTH
0
Research Products
9INDUSTRY, INNOVATION AND INFRASTRUCTURE
5
Research Products
10REDUCED INEQUALITIES
0
Research Products
11SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
12RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
13CLIMATE ACTION
0
Research Products
14LIFE BELOW WATER
0
Research Products
15LIFE ON LAND
0
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16PEACE, JUSTICE AND STRONG INSTITUTIONS
0
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17PARTNERSHIPS FOR THE GOALS
0
Research Products
Documents
15
Citations
69
h-index
5
Documents
12
Citations
89
Scholarly Output
14
Articles
9
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0/0
Supervised MSc Theses
1
Supervised PhD Theses
0
WoS Citation Count
17
Scopus Citation Count
24
Patents
0
Projects
0
WoS Citations per Publication
1.21
Scopus Citations per Publication
1.71
Open Access Source
2
Supervised Theses
1
| Journal | Count |
|---|---|
| Future Generation Computer Systems | 5 |
| IEEE Robotics and Automation Letters | 2 |
| 7th International Congress on Human-Computer Interaction Optimization and Robotic Applications ICHORA 2025 | 1 |
| Ad Hoc Networks | 1 |
| Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi | 1 |
Current Page: 1 / 2
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14 results
Scholarly Output Search Results
Now showing 1 - 10 of 14
Conference Object Forming Connected Multi-Robot Teams Utilizing Aerial Robots(Institute of Electrical and Electronics Engineers Inc., 2025) Deniz ÖzsoyellerIn this paper we study the connected multi-robot team formation problem. We consider the settings where multiple aerial and ground robots with limited communication ranges are operating in an unbounded environment. The ground robots do not have a priori knowledge about the initial locations of each other and the aerial robots. Moreover the aerial robots do not know the initial locations of the ground robots in advance. Our goal is to divide the robots into teams as quickly as possible by relocating them. Each team should be of same size and include one aerial robot assigned to it as its leader and the final configurations of the robots in each team should form a fully connected network topology. To solve this problem we present an algorithm that combines distributed coordination and online planning of the robots. We evaluate the performance of the proposed algorithm in simulations. © 2025 Elsevier B.V. All rights reserved.Article Distributed asynchronous rendezvous planning on the line for multi-agent systems(Elsevier B.V., 2024) Deniz Özsoyeller; Öznur ÖzkasapMulti-agent systems have become increasingly significant in various application areas such as search-and-rescue exploration surveillance and assembly. In this study we focus on the asynchronous autonomous rendezvous planning in multi-robot (i.e. multi-agent) systems. The objective is that the robots located in linear environments to gather rapidly at a previously unknown rendezvous location. We consider that no robot knows the positions of the other robots and its own global position. Furthermore the robot does not know its initial distance to any other robot. Our focus is on the asynchronous case where it is not required the robots to start executing the algorithm simultaneously. We propose and develop a rendezvous planning algorithm namely MAR that combines distributed coordination and online motion planning. We theoretically analyze the performance of our algorithm and show that it has a constant competitive ratio. Our extensive simulations demonstrate the performance and scalability through the analysis of the key performance metrics of interest including competitive ratio distance traveled total time number of rounds and number of meetings. Additionally we demonstrate the performance and applicability of our algorithm MAR through experimental analysis in a realistic robotic simulator. © 2024 Elsevier B.V. All rights reserved.Article Data Collection with a Team of Capacity-Constrained Unmanned Aerial Vehicles Assisted by a Mobile Recharger(Elsevier, 2025) Ozsoyeller, Deniz; Ok, Ahmet EnesWireless Sensor Networks (WSNs) have been utilized in various applications such as environmental monitoring, precision agriculture, disaster response, and military surveillance. A critical challenge that affects the system lifetime is the limited battery capacity of the sensors. In this paper, we study the sensor data collection problem with a team of unmanned aerial vehicles (UAVs) and a single unmanned ground vehicle (UGV). The UAVs work as data collectors while the UGV provides recharging and data-relaying services to the UAVs. We envision partitioned WSN scenarios, where the communication graph on the initial locations of all sensors is not connected. The objective is to minimize the total time required for the UAVs to collect the data of all sensors. We present a multi-stage online data collection algorithm that plans the paths for the UAVs that do not know the locations of the sensors in advance and are subject to both energy and storage capacity constraints. Our algorithm also plans the path of the UGV and determines the recharging sites for UGV-UAV rendezvous considering not only the limited energy capacity of the UAVs but also the total units of sensor data to be collected by each UAV. We analyze its performance theoretically, in extensive simulations, and on well-known benchmark instances.Conference Object Citation - Scopus: 3Online Planning Approaches for Multi-Robot Rendezvous(Institute of Electrical and Electronics Engineers Inc., 2024) Deniz Özsoyeller; Ozsoyeller, DenizIn this paper we study the rendezvous of a group of robots in a bounded environment. The robots do not know the locations of each other. Moreover no robot knows the distance between any pair of robots. A rendezvous location is not determined in advance. For this problem we present two algorithms with different online planning approaches: (1) cluster-search and (2) single-search. In the first approach the robots that meet continue searching as a team. Whereas in the second approach the robots that meet split and continue as single searchers. We investigate and compare the performances of our algorithms through simulations. The results show that the algorithm with the single-search approach performs better than the algorithm with the cluster-search approach. © 2024 Elsevier B.V. All rights reserved.Article Citation - WoS: 1Citation - Scopus: 1TAP: Distributed team assignment in heterogeneous multi-agent systems(ELSEVIER, 2026) Deniz Ozsoyeller; Ozsoyeller, DenizIn this article we introduce and study the problem of autonomous balanced team assignment in a heterogeneous multi-robot (i.e. multi-agent) system. The system includes n robots that are initially located in a large open area. We consider a scenario where there are two types of robots namely worker and service with limited communication ranges and specialized capabilities. The robots should be divided into teams so that each team can be assigned to a different location. The objective is to minimize the maximum distance traveled among the worker robots while ensuring that each constructed team is of equal size and has exactly one service robot to assist the worker robots in the team. Depending on the robot's initial configuration the robot can be either single or a part of a connected communication network of robots. In the former case the robot does not know the location of any other robot whereas in the latter case the robot only knows the locations of the robots in its network but not the ones outside it. For this problem we propose two algorithms TAm and TAnm that combine the distributed coordination and online motion planning methods. For assignment TAm uses a mutual decision making approach whereas TAnm uses a nonmutual decision making approach. We evaluate the performances of our strategies through extensive simulations varying the key parameters of interest including communication range environment size number of worker robots and number of service robots. The results show that TAm outperforms TAnm in sparse configurations but the performances of the algorithms approach to each other as the configuration becomes dense.Article Citation - WoS: 2Citation - Scopus: 2Distributed asynchronous rendezvous planning on the line for multi-agent systems(ELSEVIER, 2024) Deniz Ozsoyeller; Oznur Ozkasap; Özkasap, Öznur; Ozsoyeller, DenizMulti-agent systems have become increasingly significant in various application areas such as search-andrescue exploration surveillance and assembly. In this study we focus on the asynchronous autonomous rendezvous planning in multi-robot (i.e. multi-agent) systems. The objective is that the robots located in linear environments to gather rapidly at a previously unknown rendezvous location. We consider that no robot knows the positions of the other robots and its own global position. Furthermore the robot does not know its initial distance to any other robot. Our focus is on the asynchronous case where it is not required the robots to start executing the algorithm simultaneously. We propose and develop a rendezvous planning algorithm namely MAR that combines distributed coordination and online motion planning. We theoretically analyze the performance of our algorithm and show that it has a constant competitive ratio. Our extensive simulations demonstrate the performance and scalability through the analysis of the key performance metrics of interest including competitive ratio distance traveled total time number of rounds and number of meetings. Additionally we demonstrate the performance and applicability of our algorithm MAR through experimental analysis in a realistic robotic simulator.Master Thesis Çok robotlu sistemlerde görev ve yol planlaması(2025) Ok, Ahmet Enes; Özsoyeller, DenizWireless Sensor Networks (WSNs) have been utilized in a wide range of applications such as environmental monitoring, precision agriculture, industrial automation, disaster response, and military surveillance. A critical challenge that affects the system lifetime is the limited battery capacity of the sensors which is mostly consumed by data transmission. In this thesis, we study the sensor data collection problem with a team of unmanned aerial vehicles (UAVs) and a single unmanned ground vehicle (UGV). The UAVs work as data collectors while the UGV provides recharging and data-relaying services to the UAVs. We consider partitioned WSN settings, where the communication graph on the initial locations of all sensors is not connected. That is, a sensor can be single or a member of networked sensors. Each UAV has a fixed capacity that it reserves for storing sensor data. The objective is to minimize the time required for UAVs to collect the data of all sensors such that no UAV exceeds its sensor data capacity. To solve this problem, we propose a capacity-constrained data collection algorithm that plans energy-aware paths for UAVs so that they cooperatively locate the sensors and collect data from them. The algorithm also determines the UAV-UGV rendezvous locations and plans the UGV's path. Our approach combines the techniques including environment decomposition, clustering the sensors, and solving the capacitated vehicle routing problem (CVRP). In simulations, we validate the performance of our algorithm varying the key performance metrics including the number of UAVs, number of sensors, communication range, and environment size.Article Citation - WoS: 7Citation - Scopus: 8Multi-Robot Symmetric Rendezvous Search on the Line(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022) Deniz Ozsoyeller; Pratap Tokekar; Ozsoyeller, Deniz; Tokekar, PratapWe study the Symmetric Rendezvous Search Problem for a multi-robot system. There are n > 2 robots arbitrarily located on a line. Their goal is to meet somewhere on the line as quickly as possible. The robots do not know the initial location of any of the other robots or their own positions on the line. The symmetric version of the problem requires the robots to execute the same search strategy to achieve rendezvous. Therefore we solve the problem in an online fashion with a randomized strategy. In this letter we present a symmetric rendezvous algorithm which achieves a constant competitive ratio for the total distance traveled by the robots. We validate our theoretical results through simulations.Article TAP: Distributed team assignment in heterogeneous multi-agent systems(Elsevier B.V., 2026) Deniz ÖzsoyellerIn this article we introduce and study the problem of autonomous balanced team assignment in a heterogeneous multi-robot (i.e. multi-agent) system. The system includes n robots that are initially located in a large open area. We consider a scenario where there are two types of robots namely worker and service with limited communication ranges and specialized capabilities. The robots should be divided into teams so that each team can be assigned to a different location. The objective is to minimize the maximum distance traveled among the worker robots while ensuring that each constructed team is of equal size and has exactly one service robot to assist the worker robots in the team. Depending on the robot's initial configuration the robot can be either single or a part of a connected communication network of robots. In the former case the robot does not know the location of any other robot whereas in the latter case the robot only knows the locations of the robots in its network but not the ones outside it. For this problem we propose two algorithms TAm and TAnm that combine the distributed coordination and online motion planning methods. For assignment TAm uses a mutual decision making approach whereas TAnm uses a nonmutual decision making approach. We evaluate the performances of our strategies through extensive simulations varying the key parameters of interest including communication range environment size number of worker robots and number of service robots. The results show that TAm outperforms TAnm in sparse configurations but the performances of the algorithms approach to each other as the configuration becomes dense. © 2025 Elsevier B.V. All rights reserved.Article Multi-Robot Symmetric Rendezvous Search on the Line(Institute of Electrical and Electronics Engineers Inc., 2022) Deniz Özsoyeller; Pratap TokekarWe study the Symmetric Rendezvous Search Problem for a multi-robot system. There are n>2 robots arbitrarily located on a line. Their goal is to meet somewhere on the line as quickly as possible. The robots do not know the initial location of any of the other robots or their own positions on the line. The symmetric version of the problem requires the robots to execute the same search strategy to achieve rendezvous. Therefore we solve the problem in an online fashion with a randomized strategy. In this letter we present a symmetric rendezvous algorithm which achieves a constant competitive ratio for the total distance traveled by the robots. We validate our theoretical results through simulations. © 2021 Elsevier B.V. All rights reserved.
