Roland Bode

Project: vECU - Development of a virtualization framework for testing of software components of the customers AD stack Tools: C++, Python, Linux, AUTOSAR, Bazel, QEMU, Virtualization, CI/CD, Red Hat Cloud, ARM x64, Arifactory, Confluence, Jira

Project: CNN-Based 3D Object Detection with Spatiotemporal Information Modeling; Research, extension, training, and validation of SOTA DL architectures Tools: Python, PyTorch, TensorFlow, AWS Cloud, Linux, Anaconda, Git, Jupyter Lab, Bash, VirtualBox, Laxtex (Scientific writing)

Department: Research & Development; Team: Perception ADAS Project: Platooning - Function development, implementation, integration, and testing (Object/lane detection, sensor fusion, remote detection, intruder detection, etc.); Testing on vehicles Tools: C++, Python, Linux, Automotive Data and Time-Triggered Framework (ADTF), CarScope (Carmeq), CAN, Visual Studio, CMake, Matlab, Vagrant, Ansible, Docker, Conan, CI/CD, Git, SVN, VirtualBox

Department: Research & Development; Team: Perception ADAS Project: Platooning - Function development, implementation, integration, and testing (Object/lane detection, sensor fusion, remote detection, intruder detection, etc.); Testing on vehicles Tools: C++, Automotive Data and Time-Triggered Framework (ADTF), Sensor Fusion, CarScope (Carmeq), CAN, Visual Studio, CMake, Matlab, SVN

Department: Electrical Engineering and Information Technology; Chair of Information-oriented Control (ITR) Project: RAMCIP - Implementation and testing of software components for research; General robotics, 7 DOF redundant robot manipulation and control theory Tools: C++, Linux, Robot Operating System (ROS), Eigen Library, Qt Creator, Git, RQT, RVIZ, CMake, KUKA LWR 4+, Qualisys (motion capture system)

Control, perception and planning for general autonomous systems complemented by machine learning

Control theory, robotics