ASFSF2

ASFSF2 is an open-source software framework for real-time sensor fusion and state forecasting. It provides a modular platform for integrating data from diverse sensors to estimate system state and predict future behavior, with particular emphasis on autonomous systems, robotics, and advanced surveillance.

ASFSF2 expands on its predecessor by introducing a plug-in architecture, a unified data model, and a configurable fusion pipeline. The core components include a data adapter layer that ingests sensor streams, a fusion engine that combines evidence using probabilistic methods, a state estimator that generates track estimates, and a forecast module that projects future states. The framework supports traditional filters such as Kalman and particle filters, as well as learning-based components. It includes interfaces to common robotics software environments, notably ROS, and provides Python bindings alongside a high-performance C++ core.

ASFSF2 was developed by an international collaboration of researchers and engineers and is released under the Apache 2.0 license. It emphasizes cross-platform compatibility and scalable performance, with benchmarks aimed at real-time operation on multi-core systems and embedded hardware.

ASFSF2 is used in autonomous vehicles, aerial drones, industrial automation, and maritime systems, where it fuses data from LIDAR, radar, cameras, GPS/IMU, and other sources. By producing robust state estimates and short-term forecasts, it supports tasks such as navigation, obstacle avoidance, and mission planning.

Adoption has grown in academia and industry, though it requires substantial configuration and tuning to achieve optimal performance. The project maintains documentation, tutorials, and community forums to support users and developers.