Robotic Harvesting AI
Find ripe fruit and vegetables, judge ripeness, and give harvesting robots a precise pick point on every plant.
Robotic Harvesting AI for the Toughest Orchards, Greenhouses, and Fields
Deploy Anywhere, Run Everywhere
Run robotic harvesting models on arm, gripper, platform, and drone cameras, on the robot with no connection, at the edge, in the cloud, in your VPC, or via API.
One Platform, Full Adoption
Tools every harvest team can adopt, from growers and farm operators to agronomists and the robotics teams building harvesters, no separate ML team required.
Secure, Compliant, and Audit-Ready
Data stays safe with SOC 2 Type II compliance, encrypted data, HIPAA compliance, and an uptime SLA, with an image behind every pick decision in every row.
- Ripeness & Color Grading
- Fruit & Vegetable Detection
- Stem & Pick Point Keypoints
- Occluded & Clustered Fruit
- Bruise & Defect Checks
- Yield Counts by Row
“The future of automation isn't about retrofitting facilities for robots. It's about building robots that see and adapt to the real world. Vision AI makes that possible and is at the core of everything we do at Peer Robotics. With Roboflow powering our perception pipeline, we're deploying in existing facilities from day one.”
Rishabh Agarwal
CEO, Peer Robotics
Talk to a Vision AI engineer who's shipped in agriculture and robotics.
Bring us your toughest harvesting problem and we'll map a working solution.
Ask us about:
- Solution architecture that fits your crops, robots, cameras, and farm software
- A live demo on your own field or greenhouse images
- Deployment options: on the robot, edge, cloud, or VPC
- ROI modeling against picking labor, pick rate, missed and damaged fruit, and harvest timing
Over 16,000 organizations build with Roboflow.
- Rivian
- Pella
- Chobani
- USG Corporation
- BNSF Railway
- American Woodmark
Vision AI is transforming businesses
Customers across the board are solving complex challenges and driving meaningful impact.
- Automotive customer
$10 million
Saved by automatically detecting defects on the production line
- Logistics & freight company
90%
Less time spent manually tracking shipping inventory
- Building materials supplier
60%
Lower customer return rate with improved product quality
Pick Every Ripe Fruit, from the First Row to the Packing Shed
Give every harvesting robot the eyes it needs with Roboflow vision AI for robotic harvesting. Built for growers, greenhouse and orchard operators, and the robotics teams building harvesters, where fruit hides behind leaves, ripeness changes by the day, lighting shifts from row to row, and every missed or bruised fruit is lost revenue.
Find the fruit:
- Detect strawberries, tomatoes, peppers, apples, cucumbers, and other crops through leaves, stems, and tight clusters, with models trained on your own varieties and growing conditions.
- Grade ripeness by color, size, and shape, so robots pick only what is ready and leave the rest for the next pass.
- Outline each fruit with instance segmentation, so touching and partly hidden fruit are separated before the gripper moves.
Guide the pick:
- Find stems, calyxes, and cut points with keypoint detection, so the robot cuts or twists in the right place without damaging the plant.
- Send each pick point to the robot, which combines it with its depth camera to plan the approach, the same way vision powers robotic guidance on the factory floor.
- Check for bruises, rot, and misshapen fruit before or right after the pick, so damaged fruit is routed away from the packing bin.
Run the harvest:
- Count ripe and unripe fruit by row, bay, or block, so harvest crews and robots go where the crop is ready.
- Log every pick, miss, and skip with an image, so you can compare runs and see where the robot needs help.
- Feed hard cases from the field back into training, so models keep up with new varieties, seasons, and growing sites.
Bring intelligence to every harvest today. Pick the right fruit, at the right time, in the right place.
Frequently asked questions
What is robotic harvesting with Vision AI?
Robotic harvesting with Vision AI runs a trained computer vision model on the robot's cameras to find fruit, judge whether it is ripe, locate the stem and pick point, and pass that location to the robot so it can pick without damaging the fruit or the plant.
What crops and cameras does it work with?
Any crop you can photograph, from greenhouse tomatoes, peppers, cucumbers, and strawberries to orchard apples and field vegetables, using RGB cameras on the arm, gripper, or platform. Models are trained on your own crops and sites, so they learn your varieties, canopy, and lighting.
Can it run on the robot in the field?
Yes. Models can run at the edge on the robot's onboard computer, so pick decisions happen in real time without a connection in the field.
Can it integrate with our robot controller and farm software?
Yes. Roboflow returns detections, ripeness grades, and pick points to your robot's software, and sends counts and images over a REST API or webhooks to farm management tools and dashboards. The same approach powers 3D bin picking in factories and warehouses.