Boris Crnokic

About

Boris Crnokic is a researcher focused at the intersection of mobile robotics, artificial intelligence, and STEM education. His work centers on developing intelligent navigation systems for autonomous mobile robots, particularly through the application of edge detection methods and artificial neural networks for obstacle detection and sensor fusion. Crnokic’s research demonstrates how neural networks can effectively simulate obstacle detection in virtual environments and fuse data from infrared and vision sensors to improve robot navigation. His most cited paper (11 citations) compares edge detection methods for obstacle detection in mobile robot environments, establishing a foundation for practical robotic perception. Beyond technical contributions, Crnokic is a strong advocate for educational robotics, showing how platforms like Robotino and EV3 brick systems can transform STEM classrooms. His 2017 paper on mobile robots in education (6 citations) and his 2020 work on creating Python applications for robotic transport systems highlight his commitment to hands-on, project-based learning. Crnokic’s research bridges theoretical simulation with real-world application, making him a notable contributor to both autonomous navigation and modern engineering education.

Research Focus

Key Achievements

Top Papers

1. 1
   Comparision of Edge Detection Methods for Obstacles Detection in a Mobile Robot Environment

   11 citations · 2016
2. 2
   Different Applications of Mobile Robots in Education

   6 citations · 2017
3. 3
   STEM Classroom; Creating a Phyton Application for an EV3 Brick Robotic System Used to Transport 3D Printed Boxes

   5 citations · 2020
4. 4
   Artificial neural networks-based simulation of obstacle detection with a mobile robot in a virtual environment

   4 citations · 2023
5. 5
   Use of Artifical Neural Networks for Fusion of Infrared and Vision Sensors in a Mobile Robot Navigation System

   2 citations · 2020

Key Collaborators

Contact & Links