software

The ASGARD-RTFMAP software, developed for the demonstrator within the AI4CSM project, is designed for real-time data fusion of sensory inputs from cameras, LiDARs, GPS, and IMU to create a simplified 3D map of the vehicle's surroundings. This 3D map is based on detected objects in the vicinity and is designed to be easily and efficiently shared with other vehicles equipped with the same software. The software is optimized for key parameters such as minimizing data flow within the vehicle through on-sensor data preprocessing, ensuring real-time functionality, and achieving low latency in propagating newly detected obstacles into the vehicle's 3D map. Based on these parameters, a computational network was developed consisting of two processing units communicating via the ROS2 framework. The proposed system encompasses everything from sensor drivers and sensor data preprocessing to multimodal data fusion, high-level detection based on neural network models, and algorithms for 3D map creation and sharing with other vehicles. Thanks to its modularity, individual algorithms can be easily modified or replaced without affecting the overall system's functionality. Tools for verifying key performance metrics are built-in, allowing for rapid validation of the system's properties.

data fusion; artificial intelligence; feature extraction; object classification; object-based map; real-time processing; real-time obstacle sharing

1. 11. 2024

CEITEC, Purkyňova 123, B1.08

K využití výsledku jiným subjektem je vždy nutné nabytí licence

Poskytovatel licence na výsledek požaduje licenční poplatek

https://ai4csm.ceitec.cz/vysledky/