For Students

Here, you can find projects that I can offer to prospective students.






































































For Students

  • Algorithm implementation on a Real Mobile Robot In this project, you will implement algorithms on a real mobile robot. The algorithms include SLAM (simultaneous localization and mapping), navigation, planning, object detection, object tracking, calibration, etc. The robot has a 3D Lidar, depth camera and it moves with a differential drive locomotion system. You will use and learn ROS (www.ros.org). You will also collect data from the campus at different times of the semester.
    Good to know: Python.
    You will learn about: Mobile Robots, ROS, various algorithms for mobile robots.
    Level: Bsc, Msc.
  • Active Object Tracking on a Drone In this project, you will develop an active tracking algorithm in Airsim . This will be the continuation of a previous project . The drone is expected to track the object by using sensors such as RGB cameras, Lidars, etc. and then follow the trajectory of the tracked vehicle. In the project, you are expected to learn and use ROS for controlling and collecting images, use and learn modern machine learning methods for tracking (such as deep learning) and develop the environment for the simulator in AirSim (in Unreal Engine).
    Good to know: Python.
    You will learn about: Drones, simulators, ROS, object detection and tracking.
    Level: Bsc, Msc.
  • Learn to Race THE learn-to-Race Framework: You will develop algorithms to complete a race track. As an example, learn-to-Race framework can be checked. You will learn and use Reinforcement learning algorithms with perception algorithms to control the vehicle. These tracks are generally parts of other challenges, if the calendars fit, you will have the chance to submit to one of these challenges. All the codes will be written in the simulator.
    Good to know: Python.
    You will learn about: Autonomous vehicles, reinforcement learning.
    Level: Bsc, Msc or Phd.
  • Simulation in CARLA. CARLA is an open-source simulator for autonomous driving research. It has a large community of researchers. Several datasets and benchmarks exist made in CARLA. It is possible to simulate various vehicles, pedestrians, cyclists. Different environments such as highways, urban streets, country-side buildings are available. Conditions such as sunny day, rainy day, snow can be simulated with realistic photos. In this project, the students are expected to create a scenario that will be used as a benchmark for self-driving research. For details, you can contact.
    Level: Bsc, Msc or Phd.

Academic

Here, you can find research projects that I have worked in chronological order.














Projects in Academy

  • European Commission Horizon 2020 Marie Skłodowska-Curie Actions Cofund program Co-Funded Brain Circulation2 Scheme (CoCirculation2, TUBITAK 2236), (2021-?), A Generalized Adaptive Multi-Task Perception System for Mobile Platforms, Principal Investigator.
  • Toyota/Inria Project, (2017-2021), Senior Researcher.
  • EU Project (European Union), 3rd Hand Robot, (2013-2017), Senior Researcher.
  • TÜBİTAK (Turkey Scientific and Technological Research Foundation), " 111E285", Hybrid Mapping and Scene Perception by Comparison Methodology for Multi-Robots, (2012-2013), Phd Student.
  • BAP (Scientific Research Projects), "5720", Different Perception Types and Sharing via Communication for MultiRobot Systems 2011-2012, Phd Student.
  • BAP (Scientific Research Projects), "09HA210D", Scene Recognition with Multi-Robots, 2009-2010, Phd Student.
  • TÜBİTAK "107M240", Scene Recognition, Navigation and Coordination on Mobile Robots based on Attention, (2007-2010), Phd Student.