Design and Research of a Self-Propelled Pipeline Robot Based on Force Analysis and Dynamic Simulation

In pipeline inspection, traditional tethered inspection robots are severely constrained by cable length and weight, which greatly limit their travel range and accessibility. To address these issues, this paper proposes a self-propelled pipeline robot design based on force analysis and dynamic simulation, with a specific focus on solving core challenges including vertical climbing failure and poor passability in T-branch pipes. Adopting a wheeled configuration and modular design, the robot prioritizes the core demand of body motion control. Specifically, 3D modeling of the robot was first completed using SolidWorks. Subsequently, the model was imported into ADAMS for dynamic simulation, which provided a basis for optimizing the drive module and motion control strategy.To verify the robot's dynamic performance, an experimental platform with acrylic pipes was constructed. Through adjusting its body posture to surmount obstacles and select directions, the robot has demonstrated its ability to stably traverse various complex pipeline scenarios. Notably, this work offers a technical feasibility reference for the application of pipeline robots in the inspection of medium and low-pressure urban gas pipelines.

Research on Dead Reckoning Algorithm for Self-Propelled Pipeline Robots in Three-Dimensional Complex Pipelines

In the field of gas pipeline location, existing pipeline location methods mostly rely on pipeline location instruments. However, when faced with complex and curved pipeline scenarios, these methods often fail due to problems such as cable entanglement and insufficient equipment flexibility. To address this pain point, we designed a self-propelled pipeline robot. This robot can autonomously complete the location work of complex and curved pipelines in complex pipe networks without external dragging. In terms of pipeline mapping technology, traditional visual mapping and laser mapping methods are easily affected by lighting conditions and insufficient features in the confined space of pipelines, resulting in mapping drift and divergence problems. In contrast, the pipeline location method that integrates inertial navigation and wheel odometers is less affected by pipeline environmental factors. Based on this, this paper proposes a pipeline robot location method based on extended Kalman filtering (EKF). Firstly, the body attitude angle is initially obtained through an inertial measurement unit (IMU). Then, the extended Kalman filtering algorithm is used to improve the accuracy of attitude angle estimation. Finally, high-precision pipeline location is achieved by combining wheel odometers. During the testing phase, the roll wheels of the pipeline robot needed to fit tightly against the pipe wall to reduce slippage. However, excessive tightness would reduce the flexibility of motion control due to excessive friction. Therefore, a balance needed to be struck between the robot's motion capability and positioning accuracy. Experiments were conducted using the self-propelled pipeline robot in a rectangular loop pipeline, and the results verified the effectiveness of the proposed dead reckoning algorithm.