Vision Based Navigation

Vision-based navigation uses cameras to enable autonomous systems to perceive and navigate their surroundings, aiming to replicate the efficiency and adaptability of biological navigation. Current research emphasizes robust algorithms for real-time path planning in complex, unknown environments, often employing hierarchical graph structures, deep reinforcement learning, and vision transformers to handle challenges like obstacle avoidance and limited sensor data. This field is crucial for advancing autonomous robotics in diverse applications, from aerial and underwater vehicles to agricultural robots and spacecraft, by providing reliable and cost-effective navigation solutions in GPS-denied or visually challenging scenarios.