针对流体运输中的小管径管道检测与维护任务，设计并研制了一种小尺寸软体气动管道爬行机器人。该机器人采用解析隐式三周期极小曲面偏置技术，形成具有厚度的实体结构，并通过调整隐式方程参数实现结构刚度的各向异性。在此基础上，设计了径向和纵向变形驱动器，以满足机器人在管道内的灵活运动需求。为优化机器人性能，提出了一种基于MATLAB、Rhino和ABAQUS的联合参数优化框架，并利用Python脚本实现自动化参数优化流程。通过这一框架，可以有效提高机器人的运动性能和适应性。基于两种变形驱动器，设计了管道爬行机器人的整体结构，并详细阐述了制造方法和运动控制步态。实验结果表明，所设计的管道机器人能够在两种不同姿态以及一定载荷条件下稳定地沿管道运动，验证了联合参数优化框架的可行性。研究成果为后续管道爬行机器人的参数化设计和优化研究提供了有价值的参考，有助于推动软体机器人在小管径管道检测与维护领域的应用发展。

In response to the tasks of detection and maintenance in small-diameter pipeline transportation, a small-scale soft pneumatic pipeline crawling robot was designed and developed. The robot employed the technique of analytical implicit triply periodic minimal surface offset to form a solid structure with thickness, and achieved the anisotropy of structural stiffness by adjusting the parameters of implicit equations. Based on this, the radial and linear actuators were designed to meet the flexible motion requirements of the robot inside the pipeline. To optimize the performance of the robot, a joint parameter optimization framework based on MATLAB, Rhino, and ABAQUS was proposed, and an automated parameter optimization process was implemented using Python scripts. Through this framework, the motion performance and adaptability of the robot could be effectively improved. Based on two types of deformation actuators, the overall structure of the pipeline crawling robot was designed, and the manufacturing method and motion control gait were elaborated in detail. Experimental results show that the designed pipeline robot can stably move along the pipeline in two different postures and under certain load conditions, verifying the feasibility of the joint parameter optimization framework. The research results provide valuable references for the parameterized design and optimization research of subsequent pipeline crawling robots, which contributes to the application development of soft robots in the field of small-diameter pipeline detection and maintenance.