Experience
[Software Engineer]
[12.2023] - [current][Zenseact AB, Volvo., Gothenburg, Sweden]● AD/ADAS software development.
● AD/ADAS sensor calibration and perception.
[PhD Candidate]
● Development of SOTA algorithms for uneven terrain navigation.
● Research on Motion Planning and Kinodynamic Motion Planning.
● Traversability estimation,
● 3D Uneven terrain navigation framework for mobile robots.
[Robotic Software Engineer][08.2019] - [10.2020][Chicony Electronics Co., Taipei Taiwan]
● Responsible for the development of the robotic project, with the aim of achieving vision-based auto pick-place of various objects● Developed QT-based UI for interacting with the robot● Trained and validated various CNN architectures(MaskRCNN, YOLO) for custom object detection in 2D and 3D● Contributed to a few open-source ROS packages in order to include new models of industrial robots● Rewrote a custom calibration stack(ROS stacks) for different types of camera calibration tasks(Hand-Eye, Eye-Base, Camera intrinsic calib), with an automated fashion● Integrated various robot models(Staubli, Fanuc) with a Gazebo simulator, for testing and validating software in advance● Authored close to 10 ROS packages in the context of the project● Single-handedly achieved vision-based pick and place that can be ported to any ROS-supported 6DOF robots● Watch a quick demo; ● Started the RD process of building and simulating ROS2-based AGV● Built a primitive version of differential drive Mobile robot that autonomously navigates in the pre-built map(by google cartographer), uses the new Navigation2 by ROS2
[Perception Engineer]
[05.2018] - [03.2019][MIndtronic AI, Taipei Taiwan]● Responsible for autonomous vehicles and their sensor simulation under different simulators such as Gazebo and CARLA
● Took a part to design and apply the perception architecture of the autonomous vehicle
● Integrated results of perception into vector map, which was a unified representation of real-world inside the system
● Wrote a much simpler and more efficient Cost-map which was used for local path planning, obstacle avoidance, and other Grid Cell-based perception algorithms
● Achieved obstacle detection and obstacle localization in unknown environments using Lidar data
● Developed C++ code for Lidar based Object detection and tracking for autonomous driving with Kalman filter
● Actively used PCL and OpenCV for segmentation, clustering, and other manipulations on Lidar Point Clouds and Images
● Implemented several Gazebo models and world plugins including intelligent agents radar sensor plugin
Education
[12.2020] - [01.2024]PhD, Robotics[Norwegian University of Life Sciences]
[2017] - [2019]Msc, Mechatronics, Thesis: A New Real-Time 3D Detection Framework Based on Instance Segmentation[National Taipei University of Tech.]
[2016] - [2017]Msc, Mechatronics, Partially completed this Degree. [Istanbul Technical University]
Download a PDF of my CV HERE