Outdoor Environment

Research on outdoor environments focuses on enabling robots and autonomous systems to navigate and interact effectively in complex, unstructured settings. Current efforts leverage advanced perception techniques, including vision-language models, sensor fusion (RGB-D cameras, LiDAR, tactile sensors), and proprioceptive data, to achieve robust navigation, object manipulation (e.g., waste collection), and human-robot interaction. These advancements utilize machine learning algorithms, such as convolutional neural networks and model predictive control, to improve performance in tasks like obstacle avoidance, terrain traversability estimation, and sound event localization. This research has significant implications for robotics, environmental monitoring, and search and rescue operations.