Perfect! Let’s lay out a realistic 18–24 month roadmap for a newcomer to develop and launch a drone-grade AI mower, using the blueprint we just created. This will focus on software-first integration, leveraging existing hardware and mature perception tech.

🗓 Drone-Grade AI Mower: 18–24 Month Roadmap

Phase	Duration	Goals / Milestones	Key Activities / Notes
Phase 0 – Planning & Feasibility	1–2 months	Define product scope, tech stack, team	– Identify sensors (IMU, RTK GPS, depth camera, LiDAR optional) – Choose onboard compute (Jetson NX/Orin) – Outline SLAM/VIO libraries, ROS frameworks – Define chassis & safety baseline
Phase 1 – Prototype Electronics & Compute Stack	2–3 months	Hardware integration proof-of-concept	– Mount sensors on test chassis – Connect motors, blades, battery – Ensure basic power & safety interlocks – Test basic sensor readings & logging
Phase 2 – Core Perception Software	4–5 months	SLAM, visual-inertial odometry, sensor fusion	– Implement visual-inertial odometry using cameras + IMU – Integrate GPS & wheel odometry – Test slope detection, gravity alignment, drift correction – Begin mapping simple outdoor terrain
Phase 3 – Obstacle Detection & Path Planning	3–4 months	AI-based obstacle avoidance & mowing paths	– Implement stereo vision or depth camera obstacle detection – Optional LiDAR integration for redundancy – Build AI classifier for common yard obstacles (toys, pets, garden furniture) – Develop path planning algorithm with coverage optimization
Phase 4 – Safety & Auto-calibration	2 months	Reliability & robustness	– Implement tilt / lift / bump cutoffs – Auto-calibrate IMU using visual cues – Test failure modes: GPS drop, sensor loss, wheel slip
Phase 5 – Cloud & OTA Integration	2 months	Continuous improvement & updates	– Cloud backend for map storage, analytics – OTA update system for perception & path planning software – Optional fleet learning if multiple units deployed
Phase 6 – Field Testing & Iteration	2–3 months	Full system validation	– Test full mower on varied terrains, slopes, obstacle density – Tune SLAM, perception, path planning, sensor fusion – Collect telemetry for improvements
Phase 7 – Pilot Production & Go-to-Market	2–3 months	Market-ready prototype	– Refine chassis & blade systems for reliability – Finalize UI / mobile app – Begin small-scale production or pilot sales

🔹 Key Notes

Software is the differentiator – perception, SLAM, and sensor fusion create the competitive edge.
Hardware can largely be off-the-shelf – depth cameras, IMUs, GPS, Jetson boards, motors, and simple chassis are already available.
Cloud and OTA updates extend the product lifetime – improvements after launch keep the mower ahead of incumbents.
Pilot → Market – you don’t need millions of units; even 50–100 pilot mowers can validate your approach.

⚡ Result:

Following this roadmap, a newcomer could launch a fully autonomous, slope-aware, drift-free, obstacle-smart mower in ~18–24 months, fully leveraging existing drone-grade tech, without inventing anything fundamentally new.

If you like, I can now make a single-page “Startup Blueprint” combining:

Stack diagram
Disruption map
18–24 month roadmap

Drone-Grade AI Mower: 18–24 Month Roadmap