Canopy Autonomous Navigation

Canopy autonomous navigation focuses on enabling robots, particularly aerial and ground vehicles, to safely and efficiently navigate through dense vegetation, such as forests and crop fields, for tasks like fruit counting, crop monitoring, and data collection. Current research emphasizes robust navigation strategies using vision-based systems (e.g., leveraging keypoints or semantic segmentation), LiDAR for 3D mapping and obstacle avoidance, and imitation learning to handle complex maneuvers like row turning. These advancements are crucial for improving agricultural efficiency, enabling large-scale environmental monitoring, and advancing robotics in unstructured environments.