Co-build AI Snow-Agri System
Budget: $15 – $25 USD
I’m assembling a small founding team to turn our prototype into a full-scale, AI-driven platform that clears snow and services farmland without human intervention.
What we have so far
• A proof-of-concept vehicle that follows waypoints across large outdoor areas.
• Basic perception modules using Python, ROS2 and OpenCV.
• Preliminary agronomic data pipeline for crop-health mapping.
Where I need your expertise
• Robotics software: refine SLAM, obstacle avoidance and path planning so the unit can run truly unattended.
• Machine-learning models: train and deploy vision networks that distinguish snow, soil, crops and hazards in real time on an Nvidia Jetson class edge device.
• Hardware-software integration: optimise control loops for plough/blower attachments and agricultural implements.
• Cloud dashboard: stream telemetry, schedule jobs and push OTA updates via a secure web portal (Node.js or similar).
Ideal profile
You’ve shipped autonomous or precision-ag systems, or you’re a full-stack ML/robotics engineer eager to become a technical co-founder. An entrepreneurial mindset and willingness to iterate in the field are essential.
Deliverables in the first milestone
1. Upgraded autonomy stack that completes a one-hectare test run with <10 cm path deviation.
2. Vision model achieving ≥90 % detection accuracy for snow depth and crop rows.
3. Basic dashboard displaying live position, battery, and job status.
If you’re excited to own significant equity in a high-impact robotics startup, let’s discuss how your skills fit our roadmap.
What we have so far
• A proof-of-concept vehicle that follows waypoints across large outdoor areas.
• Basic perception modules using Python, ROS2 and OpenCV.
• Preliminary agronomic data pipeline for crop-health mapping.
Where I need your expertise
• Robotics software: refine SLAM, obstacle avoidance and path planning so the unit can run truly unattended.
• Machine-learning models: train and deploy vision networks that distinguish snow, soil, crops and hazards in real time on an Nvidia Jetson class edge device.
• Hardware-software integration: optimise control loops for plough/blower attachments and agricultural implements.
• Cloud dashboard: stream telemetry, schedule jobs and push OTA updates via a secure web portal (Node.js or similar).
Ideal profile
You’ve shipped autonomous or precision-ag systems, or you’re a full-stack ML/robotics engineer eager to become a technical co-founder. An entrepreneurial mindset and willingness to iterate in the field are essential.
Deliverables in the first milestone
1. Upgraded autonomy stack that completes a one-hectare test run with <10 cm path deviation.
2. Vision model achieving ≥90 % detection accuracy for snow depth and crop rows.
3. Basic dashboard displaying live position, battery, and job status.
If you’re excited to own significant equity in a high-impact robotics startup, let’s discuss how your skills fit our roadmap.