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.