Computer vision in robotics
From defect detection to autonomous navigation, build real-time vision AI solutions for the robotics industry with Ultralytics YOLO.
Trusted by the world's leading organizations
How Ultralytics YOLO tackles robotics
Real-time AI that works with your team
Built for robotics, Ultralytics YOLO streamlines workflows for precise, fast, and production-ready computer vision solutions that leverage your existing infrastructure.
- Plug-and-play deployment: Deploys with minimal overhead, cutting integration time to days.
- Detection accuracy: State-of-the-art real-time detection across objects, environments, and dynamic scenes.
- Sub-5ms inference: Edge, cloud, or on-premise deployment with 19 export formats.
- Production-ready in hours: Annotate, train, and deploy reducing time-to-market.
Try YOLO26 Inference
Drag and drop an image to see real-time object detection
Vision AI for every stage in robotics
Purpose-built solutions for every stage of your production process.
Autonomous navigation
Autonomous movement with Ultralytics YOLO
Leverage Ultralytics YOLO with the latest detection and segmentation models to give your robots the perception they need to navigate dynamic environments safely and efficiently.
- Real-time perception: Detect obstacles, paths, and landmarks on the go.
- Multi-environment ready: Works across warehouses, factories, and outdoors.
- Edge-native deployment: Runs directly on-device with no cloud dependency.
Transforming industries with vision AI
From factory floors to operating rooms, Ultralytics turns visual data into real-time decisions.
RapiD Engineering deploys seafood quality control 1 week faster with Ultralytics YOLO
See how RapiD Engineering uses Ultralytics YOLO to automate salmon inspection, detect defects in real time, and save a week of engineering work.
Project Ocean Oasis advances reef conservation with Ultralytics YOLO
Discover how Project Ocean Oasis uses Ultralytics YOLO, edge AI, and autonomous monitoring systems to scale reef conservation and ocean intelligence.
Volley powers 250+ on-court AI trainers with Ultralytics YOLO
"What's really nice is that the model performs really well in real time on edge hardware on the trainer, and we can use the same model in the cloud to run the exact same flow."
WG Tech Solutions cuts safety violations by 28% with Ultralytics YOLO and Axelera’s AI Accelerator
Learn how WG Tech Solutions managed to reduce safety violations in manufacturing by 28% leveraging Ultralytics YOLO and Axelera’s AI Accelerator
Stride delivers 1-minute equine gait analysis with Ultralytics YOLO
Learn how Stride leverages Ultralytics YOLO models for horse pose estimation, achieving a full gait analysis in under 1 minute.
Pixelabs achieves 95% recall with Ultralytics YOLO-driven automation
Learn how Pixelabs leverages Ultralytics YOLO models to automate workflows and achieve 95% recall.
SiteAssist improves site safety by processing 770K+ images with Ultralytics YOLO
Learn how SiteAssist leverages Ultralytics YOLO models to improve construction site safety.
Chef Robotics uses Ultralytics YOLO to cut food giveaway by 67%
Explore how Chef Robotics uses Ultralytics YOLO models for precise food assembly.
Cali Intelligence shortens checkout queues by 43% with Ultralytics YOLO
Explore how Cali Intelligence uses Ultralytics YOLO models to reduce retail checkout queues with object detection.
MarineSitu hits 96%+ uptime in underwater monitoring using Ultralytics YOLO
Discover how MarineSitu uses Ultralytics YOLO to transform underwater object detection.
Theia Scientific speeds up microscopy analysis 43× with Ultralytics YOLO
Discover how Theia Scientific uses Ultralytics YOLO to redefine microscopy data analysis.
eSmart Systems halves power line inspection time with Ultralytics YOLO
Discover how eSmart Systems uses Ultralytics YOLO to boost defect detection speed and transform utility inspections.
Axelera AI delivers 34 FPS edge AI inference using Ultralytics YOLO
Discover how Axelera AI uses Ultralytics YOLO to deliver fast, accurate, and efficient edge vision on Metis AI chips.
STMicroelectronics runs Ultralytics YOLO on an MCU at just 9.4 mJ per inference
Discover how STMicroelectronics efficiently deploys Ultralytics YOLO models on low-power microcontrollers to achieve accurate real-time inference at the edge.
Specialvideo reaches 99% food inspection accuracy with Ultralytics YOLO
Discover how Specialvideo uses Ultralytics YOLO models to power real-time AI food inspection, ensuring quality, reducing waste, and boosting efficiency.
Vivity AI saves $5M+ a year in industrial operations with Ultralytics YOLO
Discover how Vivity AI leverages Ultralytics YOLO models to enhance industrial automation, improving efficiency, reducing downtime, and ensuring workplace safety.
Videologic Analytics scales to 10K AI camera licenses with Ultralytics YOLO
Discover how Videologic Analytics integrates Ultralytics YOLO models to enhance video surveillance, improving detection accuracy, reducing false alarms, and optimizing real-time threat monitoring.
Prezent boosts slide detection accuracy by 34% with Ultralytics YOLO
Discover how Prezent leverages Ultralytics YOLO models to automate slide element detection, reducing processing time to under 10 seconds while preserving structure and design.
ALYCE accelerates traffic AI inference by 20% with Ultralytics YOLO
Discover how ALYCE uses Ultralytics YOLO models to enhance data accuracy, optimize urban mobility, and create AI-driven traffic solutions for sustainable, smarter cities.
Kiwitron uses Ultralytics YOLO to detect industrial hazards 30m away
Explore how Kiwitron uses Ultralytics YOLO models in its KewiEye solution to detect and address industrial hazards for better safety.
RapiD Engineering deploys seafood quality control 1 week faster with Ultralytics YOLO
See how RapiD Engineering uses Ultralytics YOLO to automate salmon inspection, detect defects in real time, and save a week of engineering work.
Project Ocean Oasis advances reef conservation with Ultralytics YOLO
Discover how Project Ocean Oasis uses Ultralytics YOLO, edge AI, and autonomous monitoring systems to scale reef conservation and ocean intelligence.
Volley powers 250+ on-court AI trainers with Ultralytics YOLO
"What's really nice is that the model performs really well in real time on edge hardware on the trainer, and we can use the same model in the cloud to run the exact same flow."
WG Tech Solutions cuts safety violations by 28% with Ultralytics YOLO and Axelera’s AI Accelerator
Learn how WG Tech Solutions managed to reduce safety violations in manufacturing by 28% leveraging Ultralytics YOLO and Axelera’s AI Accelerator
Stride delivers 1-minute equine gait analysis with Ultralytics YOLO
Learn how Stride leverages Ultralytics YOLO models for horse pose estimation, achieving a full gait analysis in under 1 minute.
Pixelabs achieves 95% recall with Ultralytics YOLO-driven automation
Learn how Pixelabs leverages Ultralytics YOLO models to automate workflows and achieve 95% recall.
SiteAssist improves site safety by processing 770K+ images with Ultralytics YOLO
Learn how SiteAssist leverages Ultralytics YOLO models to improve construction site safety.
Chef Robotics uses Ultralytics YOLO to cut food giveaway by 67%
Explore how Chef Robotics uses Ultralytics YOLO models for precise food assembly.
Cali Intelligence shortens checkout queues by 43% with Ultralytics YOLO
Explore how Cali Intelligence uses Ultralytics YOLO models to reduce retail checkout queues with object detection.
MarineSitu hits 96%+ uptime in underwater monitoring using Ultralytics YOLO
Discover how MarineSitu uses Ultralytics YOLO to transform underwater object detection.
Theia Scientific speeds up microscopy analysis 43× with Ultralytics YOLO
Discover how Theia Scientific uses Ultralytics YOLO to redefine microscopy data analysis.
eSmart Systems halves power line inspection time with Ultralytics YOLO
Discover how eSmart Systems uses Ultralytics YOLO to boost defect detection speed and transform utility inspections.
Axelera AI delivers 34 FPS edge AI inference using Ultralytics YOLO
Discover how Axelera AI uses Ultralytics YOLO to deliver fast, accurate, and efficient edge vision on Metis AI chips.
STMicroelectronics runs Ultralytics YOLO on an MCU at just 9.4 mJ per inference
Discover how STMicroelectronics efficiently deploys Ultralytics YOLO models on low-power microcontrollers to achieve accurate real-time inference at the edge.
Specialvideo reaches 99% food inspection accuracy with Ultralytics YOLO
Discover how Specialvideo uses Ultralytics YOLO models to power real-time AI food inspection, ensuring quality, reducing waste, and boosting efficiency.
Vivity AI saves $5M+ a year in industrial operations with Ultralytics YOLO
Discover how Vivity AI leverages Ultralytics YOLO models to enhance industrial automation, improving efficiency, reducing downtime, and ensuring workplace safety.
Videologic Analytics scales to 10K AI camera licenses with Ultralytics YOLO
Discover how Videologic Analytics integrates Ultralytics YOLO models to enhance video surveillance, improving detection accuracy, reducing false alarms, and optimizing real-time threat monitoring.
Prezent boosts slide detection accuracy by 34% with Ultralytics YOLO
Discover how Prezent leverages Ultralytics YOLO models to automate slide element detection, reducing processing time to under 10 seconds while preserving structure and design.
ALYCE accelerates traffic AI inference by 20% with Ultralytics YOLO
Discover how ALYCE uses Ultralytics YOLO models to enhance data accuracy, optimize urban mobility, and create AI-driven traffic solutions for sustainable, smarter cities.
Kiwitron uses Ultralytics YOLO to detect industrial hazards 30m away
Explore how Kiwitron uses Ultralytics YOLO models in its KewiEye solution to detect and address industrial hazards for better safety.
RapiD Engineering deploys seafood quality control 1 week faster with Ultralytics YOLO
See how RapiD Engineering uses Ultralytics YOLO to automate salmon inspection, detect defects in real time, and save a week of engineering work.
Project Ocean Oasis advances reef conservation with Ultralytics YOLO
Discover how Project Ocean Oasis uses Ultralytics YOLO, edge AI, and autonomous monitoring systems to scale reef conservation and ocean intelligence.
Volley powers 250+ on-court AI trainers with Ultralytics YOLO
"What's really nice is that the model performs really well in real time on edge hardware on the trainer, and we can use the same model in the cloud to run the exact same flow."
WG Tech Solutions cuts safety violations by 28% with Ultralytics YOLO and Axelera’s AI Accelerator
Learn how WG Tech Solutions managed to reduce safety violations in manufacturing by 28% leveraging Ultralytics YOLO and Axelera’s AI Accelerator
Stride delivers 1-minute equine gait analysis with Ultralytics YOLO
Learn how Stride leverages Ultralytics YOLO models for horse pose estimation, achieving a full gait analysis in under 1 minute.
Pixelabs achieves 95% recall with Ultralytics YOLO-driven automation
Learn how Pixelabs leverages Ultralytics YOLO models to automate workflows and achieve 95% recall.
SiteAssist improves site safety by processing 770K+ images with Ultralytics YOLO
Learn how SiteAssist leverages Ultralytics YOLO models to improve construction site safety.
Chef Robotics uses Ultralytics YOLO to cut food giveaway by 67%
Explore how Chef Robotics uses Ultralytics YOLO models for precise food assembly.
Cali Intelligence shortens checkout queues by 43% with Ultralytics YOLO
Explore how Cali Intelligence uses Ultralytics YOLO models to reduce retail checkout queues with object detection.
MarineSitu hits 96%+ uptime in underwater monitoring using Ultralytics YOLO
Discover how MarineSitu uses Ultralytics YOLO to transform underwater object detection.
Theia Scientific speeds up microscopy analysis 43× with Ultralytics YOLO
Discover how Theia Scientific uses Ultralytics YOLO to redefine microscopy data analysis.
eSmart Systems halves power line inspection time with Ultralytics YOLO
Discover how eSmart Systems uses Ultralytics YOLO to boost defect detection speed and transform utility inspections.
Axelera AI delivers 34 FPS edge AI inference using Ultralytics YOLO
Discover how Axelera AI uses Ultralytics YOLO to deliver fast, accurate, and efficient edge vision on Metis AI chips.
STMicroelectronics runs Ultralytics YOLO on an MCU at just 9.4 mJ per inference
Discover how STMicroelectronics efficiently deploys Ultralytics YOLO models on low-power microcontrollers to achieve accurate real-time inference at the edge.
Specialvideo reaches 99% food inspection accuracy with Ultralytics YOLO
Discover how Specialvideo uses Ultralytics YOLO models to power real-time AI food inspection, ensuring quality, reducing waste, and boosting efficiency.
Vivity AI saves $5M+ a year in industrial operations with Ultralytics YOLO
Discover how Vivity AI leverages Ultralytics YOLO models to enhance industrial automation, improving efficiency, reducing downtime, and ensuring workplace safety.
Videologic Analytics scales to 10K AI camera licenses with Ultralytics YOLO
Discover how Videologic Analytics integrates Ultralytics YOLO models to enhance video surveillance, improving detection accuracy, reducing false alarms, and optimizing real-time threat monitoring.
Prezent boosts slide detection accuracy by 34% with Ultralytics YOLO
Discover how Prezent leverages Ultralytics YOLO models to automate slide element detection, reducing processing time to under 10 seconds while preserving structure and design.
ALYCE accelerates traffic AI inference by 20% with Ultralytics YOLO
Discover how ALYCE uses Ultralytics YOLO models to enhance data accuracy, optimize urban mobility, and create AI-driven traffic solutions for sustainable, smarter cities.
Kiwitron uses Ultralytics YOLO to detect industrial hazards 30m away
Explore how Kiwitron uses Ultralytics YOLO models in its KewiEye solution to detect and address industrial hazards for better safety.
Frequently asked questions
Computer vision in robotics uses cameras and AI models to give robots the ability to perceive and understand their environment, supporting navigation, object detection, sorting, and human-robot collaboration. Ultralytics YOLO models run on robots in real time, enabling them to detect obstacles, identify objects, and adapt to dynamic environments without relying on cloud connectivity.
Computer vision in robotics is the use of AI models to interpret visual data from cameras and sensors, automating perception tasks like navigation, manipulation, and inspection. Ultralytics YOLO26 uses deep learning to recognize subtle variations that rule-based systems miss, adapting to new objects and environments.
Robotic perception covers detection, tracking, segmentation, and pose estimation for tasks like obstacle avoidance, bin-picking, and human-robot collaboration. Ultralytics YOLO26 supports all of these from one model family, with segmentation masks essential when objects touch or overlap on a conveyor or in cluttered scenes.
For robotics applications, look for a platform that handles model training on your specific tasks and environments and deploys to edge devices on the robot itself for low-latency inference. The Ultralytics Platform covers annotation, training, and deployment in one place, with enterprise licensing available for production use.
Autonomous mobile robots and drones use computer vision for navigation, person-following, obstacle avoidance, and target detection in outdoor and warehouse environments. Ultralytics YOLO supports tracking with re-identification, so robots maintain accurate tracking even in crowded scenes or when subjects are temporarily out of frame.
Yes. Ultralytics YOLO26 exports to formats for robotics edge compute including TensorRT for NVIDIA Jetson, OpenVINO for Intel CPUs, and HEF for Hailo accelerators. Lightweight YOLO26n variants run within the memory and power limits of mobile robots and drones, with enterprise licensing for production fleets.
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