Localized Coverage Planning for a Heat Transfer Tube Inspection Robot
Jiawei Li, Zhaojin Liu, Yuxiao Li, Yuanyue Li, Yimin Huang, Gang Wang
AI summary
Problem
Inspecting steam generator heat transfer tubes requires a quadruped robot to execute hundreds of precise pose transformations, but existing planning methods struggle with optimal dual-device pairing and efficient sequence planning for short operational windows.
Approach
The authors propose a four-level planning framework that uses integer programming for optimal tube pairing, low-complexity TSP algorithms for inspection sequencing, and cubic B-spline trajectory generation to ensure smooth, collision-free arm movements.
Key results
- Optimal tube pairing reduces total inspection time by over 48 minutes (18.32% improvement)
- Low-complexity TSP algorithms decrease arm operating time by 33.20 seconds (6.99% improvement)
- Four-level planning framework successfully handles dual-end-effector coverage constraints
- Framework validated through both simulations and physical experiments
Why it matters
Enhances the efficiency and reliability of critical nuclear power plant maintenance, offering a practical planning solution for industrial robots with dual-end-effectors.
Abstract
The heat transfer tubes of the steam generator are critical components of the nuclear power system and require reg- ular inspection to ensure safety. The SG-Climbot, a quadruped heat transfer tube inspection robot, is equipped with a guiding device capable of simultaneously aligning with and inspecting two heat transfer tubes. Furthermore, The guiding device must execute hundreds of pose configuration transformations to complete a lo- calized coverage inspection, thereby presenting challenges to the robot’s efficient autonomous planning. This letter presents a plan- ning framework for the SG-Climbot’s localized coverage inspection task. The framework consists of four planning levels: pair planning, position and orientation planning for the guiding device, inspec- tion sequence planning, and time-optimal trajectory planning. A maximum matching algorithm suitable for robotic arms equipped with dual execution devices to perform tasks has been proposed, achieving the optimal pairing of heat transfer tubes and reducing inspection time by over 48 minutes (18.32% improvement). In addition, we analyze the impact of various Traveling Salesman Problem (TSP) solving algorithms on sequence planning issues that require reaching numerous nodes within short operation times, reducing the arm operating time by 33.20 s (6.99% improvement). Finally, the effectiveness of the proposed planning algorithm was validated through simulations and experiments.