Computer vision in robotics

Boost automation with Ultralytics YOLO models, equipping AI-powered robotics for autonomous navigation, precise object handling, and real-time quality control.

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Ultralytics YOLO applications in robotics

Object detection

Ultralytics YOLO11 object detection model enables robots to identify, sort, and handle items.

Instance segmentation

Robotic arms can leverage YOLO11’s segmentation improving AI automation in manufacturing and logistics.

Image classification

AI-powered robotic vision systems can classify objects to automate quality control in manufacturing.

Pose estimation

Leverage YOLO11 to analyze body movement across industries for use cases such as patient rehabilitation.

OBB object detection

Oriented bounding box (OBB) detection helps drones identify object orientations for improved navigation.

Object tracking

AI-powered object tracking in robotics can enhance perception and vision for autonomous operations.

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Benefits of computer vision in robotics

01

AI robots cut 90% of manufacturing errors

By integrating real-time computer vision models like YOLO11 in robotics, manufacturers can significantly streamline workflows, improve defect detection, enhance quality control and production efficiency.

02

Robotics and vision AI to drive $4B growth

Thanks to computer vision applications in robotics and tools like YOLO11, the global robotic vision market is expected to grow from $2.6 billion in 2023 to $4 billion by 2028.

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Frequently asked questions

How is AI used in robotics?

How is computer vision used in robotics?

What are the applications of robotics in computer vision?

What is the role of deep learning in robotics?

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