iPad App (AR + LiDAR) for Measuring Wire Straightness and Length in Industrial Welding Robots
Budget: ₹37,500 – ₹75,000 INR
iPad App (AR + LiDAR) for Measuring Wire Straightness and Length in Industrial Welding Robots
Project Overview
We are developing an iOS (iPad) application for industrial welding automation.
The app should scan a welding wire/rod (default thickness 1.2 cm) using the iPad’s LiDAR or camera, analyze its real length, and detect how much it is bent (curved or molded).
If the wire bend exceeds a defined tolerance, the app should alert the operator to replace the wire.
Accuracy and reliability are key since this app will be used in a factory/robotic welding environment.
Objectives
1. Use LiDAR / ARKit depth data to capture the 3D geometry of the wire.
2. Compute:
• Actual wire length (in mm/cm)
• Deviation or bend amount compared to an ideal straight line
• Max deviation, bend percentage, and bend angle
3. Visualize results in AR — show the wire’s 3D line with color-coded bends (green = OK, red = Replace).
4. Provide PASS / REPLACE result and exportable log data.
⸻
Key Features
• Real-time scanning using iPad LiDAR or camera.
• Automatic centerline extraction from point cloud.
• Mathematical computation of straight length, arc length, and deviation.
• Tolerance setting (user-configurable threshold in mm).
• AR overlay visualization with color-coded feedback.
• Data export (JSON/CSV + snapshot image).
• Optional: fallback to camera-only mode (if LiDAR not available).
⸻
Tech Stack
Must-have:
• Swift / SwiftUI
• ARKit / RealityKit
• Vision / CoreML / Accelerate frameworks
• Strong understanding of 3D geometry, point cloud processing, and PCA/RANSAC
• Experience with iPad Pro LiDAR sensors
Nice-to-have:
• OpenCV or Metal (for high-performance image processing)
• Experience in industrial / robotic automation apps
• Familiarity with Core Data / Firebase for saving logs
⸻
Deliverables
1. Fully functional iPad app (.ipa) supporting LiDAR scanning.
2. Code repository (GitHub or Bitbucket).
3. Clean, well-documented source code (Swift).
4. Calibration & accuracy report (measured vs actual).
5. Basic user manual / video walkthrough.
6. (Optional) Fallback mode for camera-only iPads.
Project Overview
We are developing an iOS (iPad) application for industrial welding automation.
The app should scan a welding wire/rod (default thickness 1.2 cm) using the iPad’s LiDAR or camera, analyze its real length, and detect how much it is bent (curved or molded).
If the wire bend exceeds a defined tolerance, the app should alert the operator to replace the wire.
Accuracy and reliability are key since this app will be used in a factory/robotic welding environment.
Objectives
1. Use LiDAR / ARKit depth data to capture the 3D geometry of the wire.
2. Compute:
• Actual wire length (in mm/cm)
• Deviation or bend amount compared to an ideal straight line
• Max deviation, bend percentage, and bend angle
3. Visualize results in AR — show the wire’s 3D line with color-coded bends (green = OK, red = Replace).
4. Provide PASS / REPLACE result and exportable log data.
⸻
Key Features
• Real-time scanning using iPad LiDAR or camera.
• Automatic centerline extraction from point cloud.
• Mathematical computation of straight length, arc length, and deviation.
• Tolerance setting (user-configurable threshold in mm).
• AR overlay visualization with color-coded feedback.
• Data export (JSON/CSV + snapshot image).
• Optional: fallback to camera-only mode (if LiDAR not available).
⸻
Tech Stack
Must-have:
• Swift / SwiftUI
• ARKit / RealityKit
• Vision / CoreML / Accelerate frameworks
• Strong understanding of 3D geometry, point cloud processing, and PCA/RANSAC
• Experience with iPad Pro LiDAR sensors
Nice-to-have:
• OpenCV or Metal (for high-performance image processing)
• Experience in industrial / robotic automation apps
• Familiarity with Core Data / Firebase for saving logs
⸻
Deliverables
1. Fully functional iPad app (.ipa) supporting LiDAR scanning.
2. Code repository (GitHub or Bitbucket).
3. Clean, well-documented source code (Swift).
4. Calibration & accuracy report (measured vs actual).
5. Basic user manual / video walkthrough.
6. (Optional) Fallback mode for camera-only iPads.
Related categories:
iPhone
Objective C
iPad
Swift
OpenCV
iOS Development
ARKit
Computer Vision
Metal
AR / VR 3D Asset