Güler, Samet
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Guler, Samet
Samet Güler
Samet Güler
Job Title
Doç. Dr.
Email Address
samet.guler@agu.edu.tr
Main Affiliation
02.05. Elektrik & Elektronik Mühendisliği
Status
Current Staff
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ORCID ID
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WoS Researcher ID
Sustainable Development Goals
13
CLIMATE ACTION
0
Research Products
17
PARTNERSHIPS FOR THE GOALS
0
Research Products
8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
5
Research Products
12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
1
NO POVERTY
0
Research Products
6
CLEAN WATER AND SANITATION
0
Research Products
10
REDUCED INEQUALITIES
0
Research Products
14
LIFE BELOW WATER
0
Research Products
15
LIFE ON LAND
0
Research Products
5
GENDER EQUALITY
0
Research Products
4
QUALITY EDUCATION
0
Research Products
7
AFFORDABLE AND CLEAN ENERGY
0
Research Products
3
GOOD HEALTH AND WELL-BEING
0
Research Products
2
ZERO HUNGER
0
Research Products
Documents
22
Citations
221
h-index
8
Documents
20
Citations
170
Scholarly Output
16
Articles
6
Views / Downloads
1407/708
Supervised MSc Theses
3
Supervised PhD Theses
1
WoS Citation Count
68
Scopus Citation Count
90
WoS h-index
3
Scopus h-index
3
Patents
0
Projects
0
WoS Citations per Publication
4.25
Scopus Citations per Publication
5.63
Open Access Source
6
Supervised Theses
4
| Journal | Count |
|---|---|
| 19th International Conference on Informatics in Control, Automation and Robotics (ICINCO) -- JUL 14-16, 2022 -- Lisbon, PORTUGAL | 2 |
| 32nd Mediterranean Conference on Control and Automation-MED -- JUN 11-14, 2024 -- GREECE | 1 |
| Control Engineering Practice | 1 |
| European Control Conference (ECC) -- JUN 13-16, 2023 -- Bucharest, ROMANIA | 1 |
| IEEE-Asme Transactions on Mechatronics | 1 |
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16 results
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Now showing 1 - 10 of 16
Article Distributed Coverage Control with Mobile Robots: A Potential Game Approach(2023) Guler, SametEndüstriyel uygulamalarda mobil robotların kullanımı, gürbüz ve dağıtık algoritma içeren otonom çoklu-robot sistemlerine bir gereksinim oluşturmuştur. Bir robot takımının sınırlı bir alanda uzaysal-zamansal olaylara cevap vermesi anlamına gelen kapsama kontrolü bu tür sistemlerde kritik bir hedeftir. Bu çalışmada, bir grup mobil robotun doğrusal bir iş istasyonunun iki tarafında belirli lokasyonları kapsamakla görevli olduğu özel bir kapsama problemini ele alıyoruz. Problemi iyi kurgulanmış oyuncu stratejileri ile mobil robotlar arasında oynanan bir oyun olarak formalize ediyor ve ortaya çıkan yapının eşit paylaşılan fayda temelli bir potansiyel oyun olduğunu gösteriyoruz. Sunulan yapı, robotlarda anonim kimlikler ve kısıtlı algılama yeteneklerine izin veren dağıtık ve merkezi olmayan bir yapıdır. Bir grup simülasyon çalışması yaklaşımımızı doğrulamaktadır.Conference Object Practical Formation Acquisition Mechanism for Nonholonomic Leader-Follower Networks(Scitepress, 2022) Kabore, Kader Monhamady; Guler, SametA grand challenge lying ahead of the realization of multi-robot systems is the lack of an adequate coordination mechanism with reliable localization solutions. In some workspaces, external infrastructure needed for precise localization may not be always available to the MRS, e.g., GPS-denied environments, and the robots may need to rely on their onboard resources without explicit communication. We address the practical formation control of nonholonomic ground robots where external localization aids are not available. We propose a systematic framework for the formation maintenance problem that is composed of a localization module and a control module. The onboard localization module relies on heterogeneity in sensing modality comprised of ultrawideband, 2D LIDAR, and camera sensors. Particularly, we apply deep learning-based object detection algorithm to detect the bearing between robots and fuse the outcome with ultrawideband distance measurements for precise relative localization. Integration of the localization outcome into a distributed formation acquisition controller yields high performance. Furthermore, the proposed framework can eliminate the magnetometer sensor which is known to produce unreliable heading readings in some environments. We conduct several realistic simulations and real world experiments whose results validate the competency of the proposed solution.Article Efficient Relative Localization and Coordination System for Unmanned Ground Vehicle Formations Under Directed Graph Structure(Cambridge Univ Press, 2025) Kabore, Kader M.; Guler, SametOnboard localization for multi-robot systems stands as a critical area of research with wide-ranging applications. This paper introduces an innovative framework for multi-robot localization, uniquely characterized by its onboard capability, thereby negating the dependency on external infrastructure. Our approach harnesses the inherent capabilities of each robot, enabling them to localize and synchronize their movements independently. The integration of cooperative localization algorithms with formation control mechanisms empowers a group of robots to sustain a predefined formation while following a linear trajectory. The efficacy of our framework is substantiated through comprehensive simulations and real-world experimental validations. We rigorously assess the system's resilience to localization inaccuracies and external disturbances, demonstrating its adaptability and consistency in maintaining formation under diverse conditions. Furthermore, we explore the scalability of our approach, highlighting its potential to manage varying numbers of robots and its applicability in tasks such as collaborative transportation.Doctoral Thesis Çoklu Robot Sistemleri için Lokalizasyon Algoritması Tasarımı ve Gerçekleştirilmesi(2024) Kabore, Kader Monhamady; Güler, SametÇok robotlu sistemler (MRS), tek bir robot için son derece zorlayıcı olan karmaşık görevleri gerçekleştirebilir. Örneğin, iş birliğiyle taşıma, alan kapsama ve arama-kurtarma operasyonları gibi uygulamalarda, MRS en iyi seçenek olabilir. MRS, görevleri daha basit komutlara bölerek bireysel robotlara atar. Bu yapı, ölçeklenebilirlik ve tek bir hata noktasına karşı dayanıklılık gibi önemli avantajlar sağlayan merkezi olmayan yaklaşımlara ilgiyi artırmıştır. MRS'deki formasyon kontrolü, özellikle GPS'in bulunmadığı ve dış altyapının olmadığı ortamlarda güçlü robot konumlandırmasına dayanır. Dış ortamlarda GPS mutlak konumlandırma sağlayabilir ancak kapalı alanlar veya tüneller gibi ortamlarda sürü robotları için yetersiz kalabilir. Hareket yakalama sistemleri gibi kapalı alan konumlandırma çözümleri, yüksek maliyetli olup ek altyapı kurulum prosedürleri gerektirir. Bu sınırlamalar, sürü robotikleri uygulamaları için uygun, dayanıklı ve dahili konumlandırma sistemlerine olan ihtiyacı vurgulamaktadır. Bu çalışma, tamamen dahili yeteneklere dayanan, dış altyapıya bağımlılığı ortadan kaldıran yeni bir merkezi olmayan, işaretleyicisiz konumlandırma çerçevesi sunmaktadır. MRS için bir konumlandırma çözümü bulmak amacıyla, yöntemimiz, derin öğrenme ile güçlendirilmiş iş birliği temelli konumlandırma algoritmalarını formasyon kontrol mekanizmalarıyla birleştirmektedir. Önerilen çerçevenin etkinliğini doğrulamak için kapsamlı simülasyonlar ve gerçek dünya deneyleri gerçekleştirilmiştir. Sistem ölçeklenebilirliği, farklı ekip boyutlarına uyum sağlayarak test edilmiştir ve uygulamalardaki etkinliği gösterilmiştir. Bu çalışma ayrıca yer robotları için açık kaynaklı bir veri seti sunarak MRS alanında daha fazla araştırmayı teşvik etmektedir.Conference Object Range-Based Wireless Sensor Network Localization by a Circumnavigating Mobile Anchor Without Position Information(IEEE, 2024) Guler, SametTypical range-based wireless sensor network (WSN) localization approaches aim at estimating the sensor node positions by using a set of anchors with known positions. In some applications, assuming the knowledge of the anchors' positions may be impractical, and estimation of the sensors' positions in an arbitrary fixed frame may be sufficient. Considering such scenarios, we propose a WSN localization algorithm by single mobile anchor without self location information. The mobile anchor obtains distance measurements from the sensors while tracking a custom trajectory which is shown to improve the localization performance over time for high signal-to-noise ratio cases. By utilizing two stationary reference nodes within the WSN, the proposed framework generates sensor node position estimation up to translation and rotation with sufficient precision in the absence of global positioning aids. We foresee that the proposed framework can demonstrate benefits in several WSN applications ranging from internet-of-things to service robotics.Conference Object Citation - WoS: 1Citation - Scopus: 1Peer-to-Peer Localization via On-Board Sensing for Aerial Flocking(Institute of Electrical and Electronics Engineers Inc., 2020) Omar Rajab, Fat Hy; Guler, Samet; Shamma, Jeff S.The performance of mobile multi-robot systems dramatically depends on the mutual awareness of individual robots, particularly the positions of other robots. GPS and motion capture cameras are commonly used to acquire and ultimately communicate positions of robots. Such sensing schemes depend on infrastructure and restrict the capabilities of a multi-robot system, e.g., the robots cannot operate in both indoor and outdoor environments. Conversely, peer-to-peer localization algorithms can be used to free the robots from such infrastructures. In such systems, robots use on-board sensing to infer the positions of nearby robots. In this approach, it is essential to have a model of the motion of other robots. We introduce a flocking localization scheme that takes into account motion behavior exhibited by the other robots. The proposed scheme depends only on the robots' on-board sensors and computational capabilities and yields a more accurate localization solution than the peer-to-peer localization algorithms that do not take into account the flocking behavior. We verify the performance of our scheme in simulations and demonstrate experiments on two unmanned aerial vehicles. © 2022 Elsevier B.V., All rights reserved.Article Citation - WoS: 3Citation - Scopus: 5A Distributed Relative Localization Approach for Air-Ground Robot Formations With Onboard Sensing(Pergamon-Elsevier Science Ltd, 2023) Guler, Samet; Yildirim, Isa E.In a multi-robot system, diversity in the sensing and motion models of robotic entities can improve the overall performance. While such heterogeneous systems offer peculiar advantages in terms of robustness and resiliency, positioning and situational awareness of individual robots in these systems remain a challenge. In this paper, the problem of relative localization in a system composed of a drone and multiple unmanned ground vehicles which are desired to move in formation is addressed. By utilizing a leader-follower formation graph, a distance-based relative localization algorithm based on an extended Kalman filter is proposed for online estimation of the relative positions among the ground vehicles. The necessary conditions to satisfy the observability of the unmeasured states are provided. In the proposed framework, the robots exchange a limited amount of information only and do not rely on an external infrastructure, GPS, or magnetometer. Furthermore, an application of the proposed localization framework integrated to custom formation control schemes is proposed. The performance of the proposed approach is evaluated through a set of simulation and real life experiments, and its advantages and limitations are discussed by means of a comparative study.Master Thesis Erken Orman Yangını Tespiti için Otonom Heterojen Çoklu Robot Sistemi Tasarımı(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2022) Serin, Ömer Faruk; Güler, SametThe usage of autonomous multi-robot systems for human life-endangering applications is emerging. Early wildfire detection and firefighting are two example applications. In this study, a heterogenous multi-robot system is proposed for both fire detection and response. The system employs an unmanned aerial vehicle for beyond-visual line-of-sight observations and an unmanned ground robot for fire extinguisher carrying. The proposed method uses ultrawideband (UWB) communication and ranging modules for the relative localization of robots during their movements. A specially trained YOLOv7 object detection model is used for robustly detecting forest fires and smoke while a modified version of the Vector Field Histogram Plus (VFH+) algorithm on the ground robot is used for obstacle avoidance while navigating. The structural design of the system requires no odometry or mapping of the environment hence improving the applicability of the system while decreasing system complexity. Additionally, the proposed UWB localization system is shown to be robust in long-lasting operations unlike many odometry-based approaches which accumulate errors with time. Moreover, localization of the UAV is realized with only three independent UWB-based range measurements and the altitude information of the UAV. The system is tested both in a realistic simulation environment and in real experimental setups with multiple runs. Results showed that the proposed system is improvable for better detection and practical to implement even in a dense forest environment without the need for GPS sensors, odometer data, or magnetometer.Master Thesis Mesafe ve Görüntü Kullanan Dronlar ile Koordine Hedef Teşhisi ve Takibi(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2022) Alabay, Hüsnü Halid; Güler, SametRobot autonomy refers to the ability to carry out objectives by perceiving the environment and deciding on the actions required without human interruption. Although autonomous aerial robots offer big advantages in our daily life, online localization and control remain the biggest challenge lying ahead of aerial robot implementations. For single robot applications, GPS, and motion capture (mocap) systems can be utilized for outdoor and indoor applications, respectively. However, when it comes to multi-robot systems, the relative localization problem needs to be solved beyond the single robot localization problem. Furthermore, GPS signals are not available everywhere, and mocap systems limit the application space of multi-robot systems. Motivated by the industrial application scenarios, we address the relative localization and docking problem in multi-drone systems where drones do not utilize any external infrastructure for localization. We consider a two-drone system that aims at docking a target object which consists of an ultrawideband (UWB) distance sensor. The drones are equipped with UWB sensors and cameras and try to localize the target object and dock around it in a pre-defined configuration in the absence of GPS and magnetometer sensors and external infrastructures. We design an extended Kalman filter based on the dynamic model of the drone-target configuration that fuses the distance and vision sensor outputs. Particularly, we use the YOLO algorithm for the bearing detection between the drones and the target. Next, we devise and implement a switching-based distributed formation control algorithm and integrate it into the estimation algorithm. We demonstrate the performance of our algorithm in several simulation studies in a realistic Gazebo environment. Finally, we provide primary experimental results and a roadmap to the full implementation of the system.Article Citation - WoS: 19Citation - Scopus: 29Distributed Formation Control of Drones With Onboard Perception(IEEE-Inst Electrical Electronics Engineers Inc, 2022) Kabore, Kader Monhamady; Guler, SametWhile aerial vehicles offer enormous benefits in several application domains, multidrone localization and control in uncertain environments with limited onboard sensing capabilities remains an active research field. A formation control solution which does not rely on external infrastructure aids such as GPS and motion capture systems must be established based on onboard perception feedback. We address the integration of onboard perception and decision layers in a distributed formation control architecture for three-drone systems. The proposed algorithm fuses two sensor characteristics, distance, and vision, to estimate the relative positions between the drones. Particularly, we utilize the omnidirectional sensing property of the ultrawideband distance sensors and a deep learning-based bearing detection algorithm in a filter. The entire system leads to a closed-loop perception-decision framework, whose stability and convergence properties are analyzed exploiting its modular structure. Remarkably, the drones do not use a common reference frame. We verified the framework through extensive simulations in a realistic environment. Furthermore, we conducted real world experiments using two drones and proved the applicability of the proposed framework. We conjecture that our solution will prove useful in the realization of future drone swarms.
