Recently, numerous wall-climbing robots have been developed for petrochemical tank maintenance. However, most of them are difficult to be widely applied due to common problems such as poor adsorption capacity, low facade adaptability, and low detection accuracy. In order to realize automatic precise detection, an innovative wall-climbing robot system was designed. Based on magnetic circuit optimization, a passive adaptive moving mechanism that can adapt to the walls of different curvatures was proposed. In order to improve detection accuracy and efficiency, a flexible detection mechanism combining with a hooke hinge that can realize passive vertical alignment was designed to meet the detection requirements. Through the analysis of mechanical models under different working conditions, a hierarchical control system was established to complete the wall thickness and film thickness detection. The results showed that the robot could move safely and stably on the facade, as well as complete automatic precise detection.

At present, numerous wall-climbing robots have been developed, and applied in ship manufacturing for weld detection to ensure safe navigation. Limited by rigid mechanical structure and complex detection, mostly existing robots are hardly to complete weld detection by using fluorescent magnetic particles. Based on permanent magnet adsorption, a wheeled wall-climbing robot is developed to realize the stable adsorption and flexible movement on ship wall. A detection mechanism is designed using a series and parallel flexible adaptation structure to keep cross yokes and detection area close for effective detection. A unified mechanical model is established by analyzing the angle between robot attitude and gravity, to solve safe adsorption and flexible movement for different detection conditions. Integrated the multisensor information and collaboration between control component, an automatic detection control workflow conforms to the standard process is proposed. Experiments show that the robot can move on curvature wall flexibly and stably, complete the weld detection with the standard process, and clearly display the shape and depth of the small defects (groove depth ≥ 30 μm) in standard specimen.

This paper proposes a novel wheel−leg hybrid robot that can be applied on both flat and rugged terrains, it utilizes two passive transformable symmetrical wheels that combine the stability of the circular wheel and the obstacle climbing ability of the legged wheel. To minimize the number of actuators, the transformation process of the wheel is designed to be triggered passively when in contact with the obstacles. A new triggering mechanism is employed to eliminate the adverse effect of the robot’s weight on the transformation torque. The parameters of the wheel are optimized to maximize the climbing ability in low-friction conditions. The robot’s body length and angular velocity are also tuned based on the dynamic model during the obstacle climbing process. The simulation experiment results show that the robot can switch modes stably on terrain with a friction coefficient as low as 0.2, and can climb over an obstacle 3.9 times as tall as its wheel radius.

Weld detection is vital to the quality of ship construction and navigation safety, and numerous detection robots have been developed and widely applied. Focusing on the current bottleneck of robot safety, efficiency, and intelligent detection, this paper developed a wall-climbing robot that integrates multiple sensors and uses fluorescent magnetic powder for nondestructive testing. We designed a moving mechanism that can safely move on a curved surface and a serial-parallel hybrid flexible detection mechanism that incorporates a force sensor to solve the robot’s safe adsorption and a flexible detection of the curved surface to complete the flaw detection operation. We optimized the system structure and improved the overall performance of the robot by establishing a unified mechanical model for different operating conditions. Based on the collected sensor information, a multi-degree of freedom component collaborative flexible detection method with a standard detecting process was developed to complete efficient, high-quality detection. Results showed that the developed wall-climbing robot can move safely and steadily on the complex facade and can complete the flaw detection of wall welds.

In recent years, many wall-climbing robots have been developed in the field of petrochemical storage tank maintenance. However, it is difficult for most of them to be widely used due to common problems such as poor adsorption capacity, poor adaptation to elevation, and low trajectory tracking accuracy. In order to solve the problem of the robot not being able to achieve high-precision operation on curved surfaces, a new wall-climbing robot system is designed. Based on the magnetic wheel adsorption method, a passive adaptive motion mechanism that can adapt to walls with different curvatures is proposed. In order to improve the trajectory tracking accuracy of the wall-climbing robot, the kinematic model of the wall-climbing robot is simplified, a velocity compensation controller is designed, and the stability of the controller is proved by introducing the Lyapunov equation. Through experiments, the controller designed in this paper is compared with the conventional controller to verify the effectiveness and superiority of the controller. The experimental results show that the robot can move safely and stably on curved surfaces, with improved tracking accuracy and reduced trajectory deviation caused by response time lag, and meets the maintenance operation requirements of wall-climbing robots.

Rope-driven robots are increasingly used to safely and efficiently clean complex glass curtain walls. However, continuous global cleaning is difficult for most robots because of their poor performance in overcoming obstacles and adapting to curved surfaces, and an inconvenient winch calibration on complex surfaces further burdens such work. This paper presents a 3-DOF rope-driven robot and a winch self-calibration method for efficient cleaning. The robot, by integrating a 5-rope parallel configuration, a self-adaptive cleaning body, and a self-compensating driving winch, is designed to perform continuous, compliant, and accurate spatial motion on curved walls with obstacles. By deducing the kinematic model, the constraint relationship related to orderly arranged winch positions, maneuverable body positions, and accessible rope lengths is established during the robot tracking 3D trajectory. Combining the established relationship, a series of regulations are formulated for easily acquiring body positions and rope lengths, and then a self-calibration method is proposed by accurately calculating winch positions without using professional instruments. Experimental results show that the robot can perform global and precise movement on complex glass surfaces. Applying the proposed method, the maximum winch calibration error is 6.6 mm, and the maximum body tracking error is controlled within 9.6 mm.