Design and process parameter optimization of a gecko-locomotion inspired wall-climbing robot integrating experimental and CFD analysis

Purpose This study aims to design and optimize a gecko-locomotion-inspired wall-climbing robot by examining the combined effects of mechanical design parameters and operating conditions on climbing performance and adhesion reliability for inspection and manufacturing applications. Design/methodology/approach A bio-inspired wall-climbing robot was developed based on gecko locomotion principles using lightweight 3D-printed compliant structures integrated with pneumatic actuation. A Taguchi-based optimization framework was used to optimize key parameters, including suction cup diameter, linear actuator length, wall surface type, slope angle, input pressure and payload. Experimental investigations were carried out using a Taguchi L18 orthogonal array, with climbing speed and suction pressure selected as performance responses. Significant parameters were identified using signal-to-noise ratio analysis and analysis of variance. Computational fluid dynamics analysis was further conducted to examine flow behavior and adhesion characteristics under optimized conditions. Findings The results indicate that linear actuator length predominantly governs climbing speed, while input pressure, suction cup diameter and wall surface type dominantly influence suction pressure. Confirmatory experiments demonstrated performance improvements of 48.39% in climbing speed and 71.82% in suction pressure under optimized conditions. Computational fluid dynamics results revealed velocity amplification and pressure reduction due to geometric contraction and Venturi effects, corroborating the experimentally observed adhesion enhancement. Practical implications The optimized design framework and validated performance improvements can support the development of robust wall-climbing robots for real-world applications, such as façade inspection, maintenance and manufacturing-related vertical operations. Originality/value This work presents an integrated experimental–numerical optimization framework for gecko-locomotion-inspired wall-climbing robots, offering practical insights into adhesion mechanisms and supporting the development of reliable robotic systems for automated inspection and manufacturing applications.