Obstacle Detection

Obstacle detection aims to identify objects obstructing a path, crucial for safe navigation in various applications, from autonomous vehicles and robots to assistive technologies for the visually impaired. Current research emphasizes robust detection across diverse environments and conditions, employing various approaches including deep learning models (like Transformers and YOLO variants), spiking neural networks, and sensor fusion (e.g., camera-radar). These advancements are significantly impacting fields like autonomous navigation, robotics, and assistive technology by improving safety, efficiency, and accessibility.