S
Sercan Cagdas Tekkok
Researcher at İzmir University of Economics
Publications - 5
Citations - 12
Sercan Cagdas Tekkok is an academic researcher from İzmir University of Economics. The author has contributed to research in topics: Mobile robot & Initialization. The author has an hindex of 1, co-authored 5 publications receiving 6 citations.
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Proceedings ArticleDOI
The LiDAR and UWB based Source Localization and Initialization Algorithms for Autonomous Robotic Systems
TL;DR: The source localization algorithm based on the least squares techniques and the squared range measurements obtained from ultra-wide band (UWB) sensors to locate the robot in an indoor environment and the initialization algorithm which is based on light detection and Ranging scans is proposed is proposed.
Proceedings ArticleDOI
Face Detection, Tracking and Recognition with Artificial Intelligence
TL;DR: In this article, a complete system which can be used with mobile platforms has been achieved with the proposed procedure, which is based on neural networks and eigenface approach and can be implemented on mobile robots as well.
Proceedings ArticleDOI
The EKF based Localization and Initialization Algorithms with UWB and Odometry for Indoor Applications and ROS Ecosystem
TL;DR: In this article, an extension module over the Turtlebot3 libraries using ultra-wideband (UWB) sensors is proposed to solve the initialization problem along with the localization problem, which uses Light Detection and Ranging (LiDAR) and odometry to localize itself and avoid obstacles.
Proceedings ArticleDOI
The Application of Kalman Filter for Lead-Acid Battery State of Charge Estimation
TL;DR: In this article, the coulomb counting method, the linear counting model and the extended Kalman filter with nonlinear battery model are tested with both simulated and real data with a lead acid battery.
Journal ArticleDOI
A Novel Docking Algorithm Based On The LiDAR And The V-shape Features
TL;DR: Bu calisma, sarj istasyonunda sarj edilecek holonomik olmayan bir mobil platform icin LiDAR ile ozellik tabanli bir kenetlenme stratejisi sunar yalnizca V seklinde bir yapiya sahiptir.