Computer vision aids robot navigation by providing spatial awareness and object detection capabilities. Robots use cameras to capture the environment and algorithms to process the data for obstacle detection and path planning.
Techniques like SLAM (Simultaneous Localization and Mapping) combine vision and sensor data to create maps and track the robot's position within them. For autonomous robots, vision-based navigation enhances precision and adaptability in dynamic environments.
Applications include warehouse robots optimizing logistics, robotic vacuum cleaners navigating homes, and drones performing inspections or deliveries.