Automatic Lighthouse Calibration Using Conics for Indoor Robot Localization
Said Alvarado-Marin, Alexandre Abadie, Martina Balbi, Thomas Watteyne, Filip Maksimovic
AI summary
Problem
Calibrating Lighthouse localization systems traditionally requires labor-intensive manual placement of known reference points, which fails to scale for large, decentralized multi-robot swarms.
Approach
The method automatically computes the world-to-image homography by analyzing the elliptical conics traced by a moving robot, using conic intersection properties to derive a corrective transformation up to similarity.
Key results
- Achieved 7.77 mm mean positional accuracy, matching manual calibration baselines
- Demonstrated robustness to wheel slippage and varying floor/tire conditions
- Enabled fully automatic homography estimation from a single view of multiple robot-traced circles
- Validated calibration scalability across a 2×2 m² area with differential-drive robots
Why it matters
Provides a scalable, decentralized calibration solution that eliminates manual setup bottlenecks for large-scale indoor robotic swarms.
Abstract
In this letter, we propose a technique for calibrating Lighthouse localization systems using a single view of two or more coplanar circles traced by a moving robot. The calibration method leverages conic algebra to compute the homography between the Lighthouse view and the world plane, up to sim- ilarity. This approach requires minimal user intervention and is particularly suited for automatically calibrating large-scale deployments involving hundreds of mobile robots. We validate our method using a centimeter-scale differential- drive robot, utilizing 5 cm circles to calibrate a 2×2m2 area. The proposed technique achieved a mean positional accuracy of 7.77 mm, compared to the 5.37 mm accuracy of a previous calibration method based on manual measurements and known correspondences. We demonstrate that the conics traced by the robot are accurate enough for reliable homography estimation, even under varying conditions of tire material and surface type. A camera-based motion capture system served as the ground truth for all experiments. This work represents a step toward scalable and decentralized lighthouse calibration, enabling efficient 2D localization in large-scale robotic systems.