Robot Vision

Robot vision focuses on enabling robots to "see" and interpret their environment using cameras and other sensors, aiming to improve their autonomy and interaction with humans. Current research emphasizes efficient and robust object recognition and segmentation, often leveraging deep learning models like transformers and employing techniques such as zero-shot learning and active learning to reduce data requirements and improve generalization. These advancements are crucial for applications ranging from autonomous navigation and manipulation in diverse settings (e.g., homes, warehouses, surgical environments) to human-robot collaboration, driving progress in both robotics and computer vision.