Applied AI · Vision-guided robotics
Vision-guided bin picking at 80 ms end-to-end
How a YOLOv11-Seg + 3D-pose stack on a Jetson Orin Nano replaced fixed-pose jigs in a 6-DOF robotic cell — sub-80 ms latency, 99.2% accuracy, 40% throughput gain.
Computer vision & robotics perception
Computer Vision for Robotics Services
Vision systems win or lose on integration. We build perception stacks where the model, the robot, and the product engineering decision all line up.
What we do
Practical support for targeted engineering work
Yantrix delivers computer-vision systems for vision-guided pick-and-place, bin picking, defect detection on conveyors, SKU recognition, and robotic manipulation. We design the data pipeline, pick and train the model (YOLO detection, SAM-2 segmentation, custom classifiers), integrate it into ROS 2 nodes or a PLC-facing service, and ship benchmarks against the target FPS and accuracy envelope.
What problems we solve
- Reduce manual inspection and sorting with on-line visual quality control.
- Enable robotic cells to handle variable, randomly oriented, or cluttered parts.
- Replace pose fixtures and custom jigs with camera-driven perception.
- Catch defects earlier on the line and feed that signal back into process control.
Tools we use
- Ultralytics YOLOv8 / v11
- SAM-2 segmentation
- OpenCV
- PyTorch
- TensorRT
- ROS 2 perception nodes
- Intel RealSense / ZED / OAK-D cameras
- Roboflow for dataset ops
- NVIDIA Jetson Orin
Deliverables
- Production vision model with documented accuracy/latency profile
- ROS 2 perception package or gRPC / REST perception service
- Camera + lighting recommendations for the deployment environment
- Dataset, labelling guidelines, and retraining instructions
- Integration with grippers, manipulators, or PLC I/O
Use cases
Industries where this service applies
We adapt the same engineering service to different product contexts depending on the load case, packaging problem, validation target, or deployment environment.
Robotics
Relevant when the project needs focused computer vision for robotics support.
warehouse & fulfilment
Relevant when the project needs focused computer vision for robotics support.
factory QA
Relevant when the project needs focused computer vision for robotics support.
packaging
Relevant when the project needs focused computer vision for robotics support.
electronics manufacturing
Relevant when the project needs focused computer vision for robotics support.
agritech
Relevant when the project needs focused computer vision for robotics support.
Related work
Case studies connected to this service
These links help visitors move from service intent to real examples of engineering work.
Robotics design
6-DOF robotic arm design for precise pick-and-place motion
Mechanical design of a 6-DOF compact robotic arm with cycloidal gearboxes hitting ±0.1 mm repeatability at 5 kg payload — from kinematic chain to manufactured prototype.
From the blog
Articles that support this service topic
Technical articles give Google more paths into the service pages and help visitors explore adjacent engineering questions before they get in touch.
3D Printing
3D Printing Services in India: How Product Teams Build Better Prototypes Faster
Learn how 3D printing services help startups and manufacturers in India validate CAD designs, reduce prototyping cost, and build functional parts faster.
Applied AI
Deploying YOLOv11 to Jetson Orin Nano at 30 FPS
Walkthrough of shipping a segmentation-class YOLOv11 model to a Jetson Orin Nano at production latency — quantization, TensorRT conversion, and the pitfalls.
Simulation
Thermal analysis for electronics enclosures
How CFD-based thermal analysis catches hotspots, airflow dead zones, and IP67-versus-cooling trade-offs in electronics enclosures before the first prototype ships.
FAQ
Questions teams ask before they engage
Service-specific questions are useful for both users and search visibility around intent-driven queries.
What frame rate and latency can you hit on embedded hardware?
On a Jetson Orin Nano, we typically ship YOLOv11-Seg pipelines between 12-30 FPS end-to-end, with decision latency under 100 ms including camera capture, inference, and robot command. Specific numbers depend on image resolution and the target class count.
Can you retrain on our own parts and SKUs?
That's the default. We usually start with a base detector, then fine-tune on a small labelled dataset of your parts. We'll set up labelling tooling and hand you a retraining pipeline so you can keep extending it.
Do you handle the lighting and camera selection?
Yes. Vision fails most often because of the physical setup, not the model. We scope the camera, lens, lighting, and mount geometry as part of the engagement.
Start your project
Need computer vision for robotics support?
Send the problem, your current design stage, and any existing files. We can scope the work from there.