Intelligent Self-driving System (ISS) is a modular framework written in Python and C++ with the aim to build an extensible workspace tailored to research. This framework will contain both traditional and deep learning algorithms for self-driving related tasks such as perception, localization, mapping, prediction, planning, and control. The modular design with minimal dependency on external libraries can provide a transparent and clean workspace for researchers to evaluate algorithms for autonomous driving systems.
At present, the ISS framework has the capability to deploy and test algorithms using data generated by a simulator. Upon integrating sensor data from the CARLA simulator into our framework, we can evaluate a range of algorithms. Additionally, corresponding control algorithms can be employed to maneuver the simulated vehicles.
In addition to simulation results, if the sensor data from a real minicar is transmitted back to ISS via ROS, the ISS framework can leverage the sensory data to accomplish a variety of tasks and exert control over the physical minicar.