Browsing by Author "Bostanci B."

Now showing 1 - 3 of 3

Citation - Scopus: 1
The Ekf Based Localization and Initialization Algorithms With Uwb and Odometry for Indoor Applications and Ros Ecosystem
(Institute of Electrical and Electronics Engineers Inc., 2020) Oguz-Ekim P.; Bostanci B.; Tekkok S.C.; Soyunmez E.
This paper will cover some extension modules over the Turtlebot3 libraries using ultra-wideband (UWB) sensors and propose a solution to the initialization problem along with the localization problem. The Turtlebot3 already has an algorithm named move base for autonomous drive, which uses Light Detection and Ranging (LiDAR) and odometry to localize itself and avoid obstacles. However, it suffers from autonomous initialization. Therefore, ranging data from UWB sensors are used to take the initial pose of the robot to eliminate the initialization problem and advance the move base algorithm to be more robust. This data is also used in the Extended Kalman Filter (EKF) along with odometry to localize the robot. To enable wide-spread adoption, we provide an open source implementation of our algorithms and modules for the robot operating system (ROS) for real environment. Furthermore, we create an open source simulation environment for applications, which use UWB, LiDAR, and odometry data. © 2020 IEEE.
Citation - Scopus: 4
Face Detection, Tracking and Recognition With Artificial Intelligence
(Institute of Electrical and Electronics Engineers Inc., 2021) Tekkok S.C.; Soyunmez M.E.; Bostanci B.; Ekim P.O.
Due to the COVID-19 pandemic, the face masks are mandatory everywhere so it might be beneficial to automatize the detection and tracking of whether people wear a mask or not with the help of the computer vision. Furthermore, it can be implemented on mobile robots as well. Additionally, face recognition of people is discussed with two different techniques which are based on neural networks and eigenface approach in this study. Hence, a complete system which can be used with mobile platforms has been achieved with the proposed procedure. © 2021 IEEE.
Citation - WoS: 9
Citation - Scopus: 16
The Lidar and Uwb Based Source Localization and Initialization Algorithms for Autonomous Robotic Systems
(Institute of Electrical and Electronics Engineers Inc., 2019) Bostanci B.; Tekkok S.C.; Soyunmez E.; Oguz-Ekim P.; Yeganli F.
This paper covers 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. Additionally, the initialization algorithm which is based on light detection and Ranging (LiDAR) scans is proposed. It takes the advantage of the estimated location to find the initial orientation of the robot with respect to the previously obtained map. Thus, the crucial problem of the autonomous initialization and localization in robotics is solved. To enable wide-spread adoption, we provide an open source implementation of our algorithms and the modules for the robot operating system (ROS) for real environment. Furthermore, an open source simulation environment is created for applications which employ UWB/LiDAR data. © 2019 Chamber of Turkish Electrical Engineers.