Free Space Detection

Free space detection aims to identify navigable areas within an environment, crucial for autonomous systems like vehicles and robots. Current research emphasizes improving accuracy and robustness through advanced deep learning architectures, including those employing heterogeneous feature fusion, data augmentation techniques (like diffusion models), and attention mechanisms to integrate diverse sensor data (e.g., LiDAR, RGB images, radar). These advancements are significantly impacting various fields, from autonomous driving and robotics to public safety applications involving radioactive material localization, by enabling safer and more efficient operation in complex and dynamic environments.