A Real-Time 6-DoF Posture Estimation Method for High-Speed 6-Axis Industrial Manipulator Control Using a 2D Laser Profiler
Tao Chen, Pei-Chun Lin
AI summary
Problem
Camera-based 6-DoF estimation suffers from high latency and low operating frequency, while laser trackers offer high speed and accuracy but are prohibitively expensive for widespread industrial use.
Approach
The method uses a single 2D laser profiler to scan a custom gauge with known geometry, deriving a closed-form mathematical solution for 6-DoF pose that is refined via maximum likelihood estimation and synchronized with a microcontroller for real-time processing.
Key results
- Closed-form 6-DoF solution refined via MLE achieves computation times under 1 ms
- Custom gauge design with five corner points optimally balances fabrication complexity and estimation accuracy
- Demonstrates superior operating frequency and lower latency compared to camera-based benchmark systems
- Successfully validated through real-time closed-loop position control of a six-axis industrial manipulator
Why it matters
Offers a cost-effective, high-frequency alternative to expensive laser trackers and low-frequency vision systems, enabling precise real-time control for dynamic industrial robotics.
Abstract
6-DoF posture estimation is a critical technique in robotics. However, a significant gap exists between the two primary approaches—camera-based methods and laser tracker systems—in terms of cost and performance. To bridge this gap, this work proposes a method to calculate the 6-DoF posture of a manipulator’s end-effector using the 2D profile of a custom- designed metallic gauge. The core principle relies on a one- to-one correspondence between the measured profile and the manipulator’s posture. A mathematical model was developed to derive a closed-form solution, which is further refined via maximum likelihood estimation to enhance robustness and ac- curacy. Simulation studies assessed the influence of geometric parameters on estimation accuracy and noise robustness. Real- world experiments demonstrated that the refined solution signifi- cantly outperforms the closed-form solution alone. Furthermore, a speed benchmark against a camera-based system highlighted the proposed method’s advantage in operating frequency. Finally, the method was successfully integrated into a real-time position control task for a 6-axis industrial manipulator, verifying its practical applicability in real-time robotic control.