07 Vision Systems, Sensors & Adaptive Programming

🤖 Robot Programming Ch.7: Vision Systems, Sensors & Adaptive Programming (2026) Teaching the robot to see, feel, and adapt. This chapter transforms your robot from a blind repeater into an intelligent machine that reacts to the real world — picking random parts, inspecting quality, and adjusting force in real time. What you'll learn: 📷 2D vision fundamentals: cameras, lighting, lenses — and why lighting is 80% of success 🎯 Vision-guided picking: the complete 8-step pipeline from trigger to pick with validation 🔍 Common vision tools: pattern matching, blob analysis, edge detection, barcode/OCR reading 💪 Force/torque sensing: insertion tasks, polishing, assembly — controlling force not just position 🏭 Conveyor tracking: picking moving parts in sync with a belt encoder 🧠 Adaptive programming: programs that adjust based on sensor feedback, not just taught points The truth about vision: A $3K camera with $2K lighting will outperform a $10K camera with ambient lighting every time. Budget 30-40% of your vision system cost on controlled lighting. This single tip will save you months of frustration. Multi-OEM code included: Complete vision-guided pick in ABB RAPID — 60+ lines with camera trigger, result validation (score, range, angle checks), offset calculation, and error handling for timeout and low confidence. Vision system comparison: Cognex In-Sight, Keyence IV3, FANUC iRVision, ABB Integrated Vision, Photoneo 3D, SICK PLB — cost, speed, resolution, and best application for each. Debugging checklist when vision fails: Check lighting first — always Check focus at working distance Check calibration with known object Check communication signals Check part presentation consistency Check score threshold — too high? Check trigger timing — vibration settled? Save failed images for analysis 📘 From "Robot Programming: From Fundamentals to Production-Ready Code" — First Edition 2026 by Shuvash Aryal | Geek Engineering (GeEn)