Development of a Pipeline Surface Curvature Detection Method for Biped Climbing Robotic System

Daily cleaning and maintenance of high-rise buildings' curved surfaces, particularly on irregular pipeline exteriors, imposes high risks for human workers. While climbing robots are increasingly used for cleaning flat surfaces in buildings, they encounter challenges in automatically aligning the suckers with target surface, which limits their applicability for cleaning curved surfaces. This paper proposes a novel low-cost pipeline curvature detection method and applies it to a wireless biped curve-surface climbing robot (BCCR) with a five-degree-of-freedom (5-DOF) structure. The BCCR features adaptive vacuum suction cups. It is equipped with multiple laser sensors on the suction modules to detect the curvature of various surfaces. These sensors collect real-time distance information between the end-effector and pipeline surface, enabling the robot to adjust the posture and securely adhere to the surfaces. The robotic system is integrated with a wireless communication system for remote control and real-time monitoring, enhancing the robot's operational efficiency and flexibility. Experimental results demonstrate that the robot can effectively navigate and attach to the exterior surface of pipelines, providing reliable and efficient cleaning solutions for high-risk maintenance tasks.