Environment Recognition

Environment recognition encompasses the automated identification and understanding of surrounding environments using various sensor modalities, aiming to create accurate representations for diverse applications. Current research focuses on developing robust methods for environment classification across different data types (audio, visual, sensor readings), employing techniques like deep learning (including convolutional and recurrent neural networks, transformers), and symbolic reasoning to improve accuracy and explainability. These advancements have significant implications for robotics, forensic science, autonomous driving, and environmental monitoring, enabling more effective interaction with and understanding of the physical world.