This is the official space for projects open-sourced and maintained by the Institute for Automotive Engineering (ika).
As an institute of RWTH Aachen University, ika is leading education and research in automotive engineering. At ika, we research future, efficient, sustainable, and safe solutions for a wide range of mobility use cases. Our research spans the entire vehicle and mobility system, including:
- Vehicle Concepts & HMI
- Vehicle Dynamics & Acoustics
- Energy Management & Drivetrains
- Vehicle Intelligence & Automated Driving
- Traffic Psychology & Acceptance
Important
If you would like to learn more about how you can use our tools or how we can support your efforts in any of these domains, feel free to reach out to us!
📧 [email protected]
| Repository | Description | ||
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| mqtt_client | Bi-directional bridge between ROS & MQTT: Connect your robots running ROS and robustly exchange native ROS messages over any network |  Paper (2022) |
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| mqtt-in-docker | Secure IoT communication with MQTT and Docker: Learn how to combine the MQTT protocol with Docker and a Public Key Infrastructure for secure IoT communication |  |
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| etsi_its_messages | ROS support for ETSI ITS messages: Use standardized ETSI ITS messages for V2X communication in ROS systems |  Preprint |
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| Repository | Description | ||
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| CARLOS | An Open, Modular, and Scalable Simulation Framework for the Development and Testing of Software for C-ITS: Take CARLA simulation to the next level |  Paper (2024) |
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| Repository | Description | ||
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| docker-ros | Microservice-based Development and Deployment: Containerize your ROS / ROS 2 packages or package stacks for simple deployment |  Paper (2024) |
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| docker-ros-ml-images | Lightweight Docker images for machine learning: Use our lightweight multi-arch machine learning-enabled ROS Docker images for your development and deployment |  Paper (2024) |
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| docker-run | Official Docker CLI with useful defaults: Simplify your container-driven development and deployment by using docker-run for your container interaction |  Paper (2024) |
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| Repository | Description | ||
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| libtensorflow_cc | Pre-built TensorFlow C++ API: Easily deploy TensorFlow deep learning models in high-performance C++ applications |  |
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| tensorflow_cpp | Helpful model wrappers around TensorFlow C++ API: Easily load, inspect, and run your TensorFlow deep learning models from C++ applications |  |
| Repository | Description | ||
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| acdc / acdc-notebooks |
ACDC MOOC: Gain practical experience in automated driving with coding exercises that teach you the latest methods and tools |   edX Course |
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| acdc-research-projects | Research projects of ACDC MOOC: Learn how to apply automated driving-related methods and tools by conducting a research project on your own |  edX Course |
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| Repository | Description | ||
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| ros2-pkg-create | Powerful ROS 2 Package Generator: Easily generate complex ROS 2 C++ and Python packages |  |
| Repository | Description | ||
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| Cam2BEV | Surround View Computation based on Hybrid AI: Enable vehicles to understand their environment by leveraging Hybrid AI methods to process camera data |  Paper (2020) |
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| EviLOG / DEviLOG |
Uncertainty-aware environment modeling: Estimate occupied and free space based on lidar point clouds |   Paper (2021) Paper (2022) |
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| Point-Cloud-Compression | Compression of lidar data: Efficiently transmit point clouds between connected and automated vehicles |  Paper (2022) |
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| MultiCorrupt | A multi-modal robustness dataset and benchmark of lidar-camera fusion for 3D object detection: Evaluate the robustness of multi-modal 3D object detectors against ten distinct types of corruptions |  Paper (2024) Trailer Poster |
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| Repository | Description | ||
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| ros2-v2x-benchmarking-suite | Benchmarking suite for V2X case study: Benchmark latencies between two connected robots in a V2X case study on edge-cloud lidar object detection |  Paper (2022) |
| Repository | Description | ||
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| RobotKube | Fully automated fleet orchestration: Orchestrate large-scale cooperative multi-robot systems with Kubernetes and the Robot Operating System |  Paper (2023) |
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| Repository | Description | ||
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| omega_format | Object list-based reference data format: Enable automated algorithms for scenario extraction and validation and verification of ADAS |  |
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| RoadGeneration | ASAM OpenDrive map generator: Generate variations of complex ASAM OpenDRIVE maps using a simplified logical description format |  Paper (2020) Paper (2022) |
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| SimDriver | Closed-loop traffic agent model: Simulate responsive agents in exact and closed-loop microscopic traffic scenarios | |
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| agent-model-integration | Integration of an Agent Model into an Open Simulation Architecture for Scenario-Based Testing of Automated Vehicles: Deploy driver models in your custom simulation environment |  |
