Design and Control of Dual‐Body Negative Pressure Ground‐Wall Transition Robot

This article presents a novel dual‐body negative‐pressure ground‐wall transition robot (DNPTR) aimed at expanding the application scenarios of climbing robots to meet the functional requirements of obstacle traversal and wall transition in high‐altitude operations. As a typical representative of highly nonlinear and multivariable strongly coupled systems, the wall transition actions of the DNPTR are analyzed and planned based on the mechanical structure characteristics. Subsequently, unified kinematic and dynamic models of the bipedal negative‐pressure climbing robot are established. To improve the automation and ensure safe, efficient operation of climbing robots, effective trajectory tracking control for the DNPTR is crucial. Addressing challenges such as model parameter uncertainties and external disturbances, this study proposes an adaptive trajectory tracking control method based on a radial basis function neural network. The method integrates a boundary layer with an improved exponential reaching law, forming a non‐singular terminal sliding mode control strategy. Using Lyapunov theory, the global asymptotic stability of the system is verified. Both simulation and experimental results demonstrate that this approach achieves faster convergence and effectively suppresses oscillations during trajectory tracking. This research is of practical importance, offering valuable guidance for the design of high‐accuracy, robust trajectory‐tracking controllers for dual‐body climbing robots.