Stair Detection
Stair detection research focuses on enabling robots and assistive technologies to reliably identify staircases in diverse environments. Current methods heavily utilize deep learning, often employing multi-task architectures that combine semantic segmentation and object detection, or cascaded pipelines integrating line segment detection for improved accuracy and robustness. These advancements aim to overcome challenges posed by varying lighting conditions, occlusions, and diverse staircase structures, ultimately improving the navigation capabilities of autonomous systems and aiding visually impaired individuals. The speed and accuracy of these algorithms are key performance indicators, with recent work achieving real-time performance suitable for many applications.