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Computer Vision and AI for Industrial Robots
Expand Your Robots' Capabilities with Computer Vision and AI
We develop computer vision solutions that integrate seamlessly with various robot control systems, including ROS (Robot Operating System). Our technology enhances robot capabilities—from object recognition to environmental analysis.
We handle the entire process, from developing computer vision models to integrating and optimizing them for real-time performance on your hardware.
We handle the entire process, from developing computer vision models to integrating and optimizing them for real-time performance on your hardware.
WHO IS IT FOR?
- Industrial Companies: Automating assembly, sorting, and inspection processes.
- Robotics Startups: Building MVPs and prototypes, including ROS-based solutions.
- Logistics Companies: Managing warehouse robots and automating cargo inspection.
WHAT WE OFFER
Object Detection and Classification
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Real-Time Recognition
We use models like YOLOv8–YOLOv11 to accurately detect object type, position, and size. -
Performance in Challenging Conditions
Our models work under low lighting, partial occlusion, and complex backgrounds. -
Examples
→ Recognizing items on conveyor belts.
→ Identifying components in production lines.
→ Detecting cargo defects.
Segmentation and Environmental Analysis
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Object Segmentation
Detecting object contours to analyze shapes, volumes, and boundaries. -
3D Reconstruction
→ Building point clouds for further analysis (leveraging ArUco markers and depth vision technologies).
→ Integrating CV with lidar data for SLAM and localization tasks. -
Use Cases
→ Surface defect detection on cargo.
→ Object size measurement.
→ Analyzing objects for robotic grasping.
Integration of Computer Vision Models with ROS
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Developing ROS Nodes for CV
→ Processing 2D and RGBD video streams from cameras like Zed2i.
→ Transmitting vision data to other system components.
→ Synchronizing ROS messages (sensor_msgs, vision_msgs). -
Integration with ROS 1 and ROS 2
→ Supporting both legacy and modern architectures.
→ Seamless compatibility with OpenCV and PCL. -
Use Cases
→ Real-time object detection and sorting on production lines.
→ Computer vision for mobile robot navigation.
Optimization of Computer Vision Solutions
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Model Optimization
→ Adapting models for Jetson Orin Nano, NVIDIA Xavier, and Intel Movidius using TensorRT or ONNX.
→ Quantization to reduce computational load. -
Latency Reduction
Optimizing pipelines for real-time performance with GPU acceleration. -
Use Cases
→ Reducing frame processing time to 25 ms on Jetson Xavier for robotic manipulators.
→ Ensuring uninterrupted 30 FPS operation in ROS-based systems.
WHY CHOOSE US?
REAL-WORLD EXPERIENCE
We have worked on object sorting, cargo inspection, and robot navigation in warehouses and production facilities.
TECHNICAL EXPERTISE
We use advanced CV models (YOLOv8–YOLOv11, ResNet50, MobileNetV2) and have deep knowledge of ROS, from developing custom packages to optimizing existing solutions.
FLEXIBILITY AND ADAPTATION
We tailor solutions to your specific needs and provide full support at every stage of implementation.
our cases
How we work
1
Task analysis
We study your requirements and determine the key parameters of the system
2
Development
We create ROS nodes and CV models adapted to your task
3
Testing
We conduct a simulation in the Gazebo and tests on real equipment
4
Implementation and maintenance
We deploy the solution from the client, train staff, monitor and retrain models
technology blog
Are you ready to give your works a vision?
Contact us to discuss your task and get a solution that integrates with ROS and works in real conditions!
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