Search Results (26)

This research paper presents the design and implementation of a wall-climbing robot for safety-critical inspection systems. The robot incorporates wheels embedded with neodymium magnets and a rocker-bogie mechanism to navigate vertical and inverted surfaces. The key novelty of this work lies in the use of a simplified, sensorless rocker-bogie mechanism that enables smooth inner and outer transitions without depending on complex control systems. This study addresses the following research questions: (1) How can a wall-climbing robot achieve stable transitions using a rocker-bogie mechanism? (2) What is the maximum payload capacity of the robot without compromising mobility and stability? (3) How will the robot behave during obstacle climbing? Weighing 2.08 Kg, the robot can easily carry a payload of 1.56 Kg, and can climb obstacles of up to 20 mm. The robot system is controlled wirelessly via a Bluetooth module. During experimental testing, the robot performed different types of transitions with stability and reliable control. Future developments could include hybrid adhesion systems for unstructured situations and AI-assisted navigation. Full article

Stable adhesion on non-magnetic, steep, and irregular underwater surfaces (e.g., concrete dams with cracks or biofilms) remains a challenge for inspection robots. This study develops a novel adsorption mechanism based on the synergistic operation of a Venturi-ejector and a composite suction cup. The mechanism utilizes the Venturi effect to generate stable negative pressure via hydrodynamic entrainment and innovatively adopts a composite suction cup—comprising a rigid base and a dual-layer EPDM sponge (closed-cell + open-cell)—to achieve adaptive sealing, thereby reliably applying the efficient negative-pressure generation capability to rough underwater surfaces. Theoretical modeling established the quantitative relationship between adsorption force (F) and key parameters (nozzle/throat diameters, suction cup radius). CFD simulations revealed optimal adsorption at a nozzle diameter of 4.4 mm and throat diameter of 5.8 mm, achieving a peak simulated F of 520 N. Experiments demonstrated a maximum F of 417.9 N at 88.9 W power. The composite seal significantly reduced leakage on high-roughness surfaces (Ra ≥ 6 mm) compared to single-layer designs. Integrated into an inspection robot, the system provided stable adhesion (>600 N per single adsorption device) on vertical walls and reliable operation under real-world conditions at Balnetan Dam, enabling mechanical-arm-assisted maintenance. Full article

A wall-climbing robot is an electromechanical device capable of autonomous or semi-autonomous movement on intricate vertical surfaces (e.g., walls, glass facades, pipelines, ceilings, etc.), typically incorporating sensing and adaptive control systems to enhance task performance. It is designed to perform tasks such as inspection, cleaning, maintenance, and rescue while maintaining stable adhesion to the surface. Its applications span various sectors, including industrial maintenance, marine engineering, and aerospace manufacturing. This paper provides a systematic review of the physical principles and scalability of various attachment methods used in wall-climbing robots, with a focus on the applicability and limitations of different attachment mechanisms in relation to robot size and structural design. For specific attachment methods, the design and compatibility of motion and attachment mechanisms are analyzed to offer design guidance for wall-climbing robots tailored to different operational tasks. Additionally, this paper reviews localization and path planning methods for wall-climbing robots, comparing graph search, sampling-based, and feedback-based algorithms to guide strategy selection across varying environments and tasks. Finally, this paper outlines future development trends in wall-climbing robots, including the diversification of locomotion mechanisms, hybridization of attachment systems, and advancements in intelligent localization and path planning. This work provides a comprehensive theoretical foundation and practical reference for the design and application of wall-climbing robots. Full article

Most of the developed and studied service robots for vertical locomotion, as visual inspection, are made up by a rigid body with legs, wheels, or both. Thus, the robot can only displace over regular and/or flat surfaces since it is not able to adapt to the irregularities and projections of the wall. Therefore, this paper presents the design and analysis of an adaptable robot for vertical locomotion service tasks, which has a body made up of four wheeled legs that can easily adapt to the different irregularities and projections of building facades. The robot uses an Electric Ducted Fan (EDF) as the vortex adhesion system. Each leg has a rubber cover, which allows a higher mechanical adaptability of the robot over different irregularities of the wall. Theoretical backgrounds and open issues are addressed by considering some challenging problems such as mechanical adaptability modeling as well as kinematic and static analysis. Laser sensors are mounted over the robot to measure the adaptability of the robot, between the legs and body, at each time of the experimental tests for vertical locomotion. Full article

Wall-climbing robots have broad application potential in industrial equipment inspection, chemical storage tank maintenance, and high-altitude operations. However, their practical implementation is challenged by the robots’ adhesion requirements in complex wall environments. This study uses a systematic methodology integrating computational simulation and experimental validation to design and optimize a magnetic adsorption system for wall-climbing robots. Firstly, an adjustable suspended magnetic adhesion unit is designed to achieve intelligent control of a wall-climbing robot’s adhesion force on a wall surface. The Maxwell software (AnsysEM21.1) is used to simulate and analyze the critical parameters of the magnetic adsorption unit, including the thickness of the magnet and yoke, as well as the distance and angle between the magnet and the wall surface. Then, a magnetic wheel is designed for the wall-climbing robot based on the optimization of the structure and parameters of the magnetic adhesion unit. The absorption and demagnetization of the magnetic wheels are achieved by rotating the magnetic absorption unit. Subsequently, the simulation results are verified on the experimental platform, and adhesion performance tests are conducted on both standard flat surfaces and inclined walls. The results show that the optimized single magnetic adhesion unit gives the wall-climbing robot an adhesion force of 2767 N under normal working conditions, with a simulation experiment error margin as low as 8.3%. These results both provide theoretical guidance and highlight practical methodologies for developing high-performance magnetic adsorption systems in complex operational environments. Full article

The maintenance of the surface of steel structures is crucial for ensuring the quality of shipbuilding cranes. Various types of wall-climbing robots have been proposed for inspecting diverse structures, including ships and offshore installations. Given that these robots often operate in outdoor environments, their performance is significantly influenced by wind conditions. Consequently, understanding the impact of wind loads on these robots is essential for developing structurally sound designs. In this study, SolidWorks software was utilized to model both the wall-climbing robot and crane, while numerical simulations were conducted to investigate the aerodynamic performance of the magnetic wall-climbing inspection robot under wind load. Subsequently, a MATLAB program was developed to simulate both the time history and spectrum of wind speed affecting the wall-climbing inspection robot. The resulting wind speed time-history curve was analyzed using a time-history analysis method to simulate wind pressure effects. Finally, modal analysis was performed to determine the natural frequency and vibration modes of the frame in order to ensure dynamic stability for the robot. The analysis revealed that wind pressure predominantly concentrates on the front section of the vehicle body, with significant eddy currents observed on its windward side, leeward side, and top surface. Following optimization efforts on the robot’s structure resulted in a reduction in vortex formation; consequently, compared to pre-optimization conditions during pulsating wind simulations, there was a 99.19% decrease in induced vibration displacement within the optimized inspection robot body. Modal analysis indicated substantial differences between the first six non-rigid natural frequencies of this vehicle body and those associated with its servo motor frequencies—indicating no risk of resonance occurring. This study employs finite element analysis techniques to assess stability under varying wind loads while verifying structural safety for this wall-climbing inspection robot. Full article

Various marine engineering facilities have been eroded by marine organisms and wind waves for a long time, resulting in different types of damage to the surface of marine engineering facilities, such as the pile legs of offshore platforms. Therefore, in order to carry out safety inspections and other work on marine engineering facilities, a small amphibious robot structure system and a set of control systems adapted to it are independently developed. Various problems such as the modular design of the structure, composite motion mode, adsorption stability, wall adaptability of the crawling mode, and flaw localization have been solved by means of three-dimensional modeling, mechanical analysis, simulation, and electronic design. At the same time, a set of control systems including hardware and software is developed for the amphibious robot. In order to improve the stability and efficiency of the amphibious robot working underwater, a sliding mode control algorithm based on the exponential reaching law and saturation function is designed. For the fixed depth and fixed heading control functions, the sliding mode control algorithm and the PID control algorithm are simulated and compared. Finally, several types of experiments are carried out for the amphibious robot. The simulation and experimental results show that all the functions of the amphibious robot meet work requirements, such as the motion performance of the composite motion mode. Compared with the PID control algorithm, the sliding mode control algorithm has a faster response speed and better stability, which is conducive to the efficient and stable work of the amphibious robot underwater. Full article

Regular inspections and hull cleanings are essential to prevent bio-fouling on ships. However, traditional cleaning methods such as brush cleaning and high-pressure water-jet cleaning at docks are ineffective in cleaning niche areas like bow thrusters and sea chests. Consequently, cleaning robots based on brushes and water jets have been developed to effectively remove bio-fouling. However, there are concerns that brushes may damage hull coatings, allowing bio-fouling to penetrate the damaged areas. In this study, removal experiments were conducted to identify the most dominant factor in fouling removal using water jet-based cleaning, in preparation for the development of non-contact cavitation high-pressure water jet-cleaning robots. The Taguchi method was used to identify influential factors and generate experimental conditions, and equipment systems for the removal experiments were established. Image analysis was performed to assess the bio-fouling occurrences on each specimen before and after cleaning, and numerical simulations of the nozzle were conducted to estimate stagnation pressure and wall shear stress to confirm the effect on micro-fouling removal. The results indicated that pump pressure is the most influential factor in removing large bio-fouling organisms grown in marine environments and on ship surfaces. Full article

With the passage of time during pipeline operation, a substantial number of impurities accumulate and adhere to the inner wall of the pipeline. This deposition hinders the pipeline’s ability to function correctly, thereby posing significant hidden risks to people’s lives and the safety of their property. This article focuses on employing pipeline robots for internal cleaning. It examines the jet cleaning process of the spiral-driven pipeline inspection and cleaning robot, aiming to determine the optimal motion state and cleaning parameters for the device within the pipeline. The findings are verified and analyzed through experiments. It was observed that the cleaning effect is enhanced, with a target surface distance of approximately 12- to 13-times the diameter of the nozzle outlet (around 25 mm). In addition, an incident angle of 15° yields favorable cleaning results, with a maximum shear force exerted on the target surface of approximately 0.11 MPa. Ensuring that the pipelines operate reasonably and stably, thus guaranteeing their safe functioning and preventing significant economic and environmental damage, holds immense value. Full article

Recent advances in roller coasters accelerate the creation of complex tracks to provide stimulation and excitement for humans. As the main load-bearing component, tracks are prone to damage such as loose connecting bolts, paint peeling, corroded sleeper welds, corroded butt welds, reduced track wall thickness and surface cracks under complex environments and long-term alternating loads. However, inspection of the roller coaster tracks, especially the high-altitude rolling tracks, is a crucial problem that traditional manual detection methods have difficulty solving. In addition, traditional inspection is labor-intensive, time-consuming, and provides only discrete information. Here, a concept of the multifunctional detection robot with a mechanical structure, electrical control system, camera, electromagnetic ultrasonic probes and an array of eddy current probes for detecting large roller coaster tracks is reported. By optimizing the design layout, integrating multiple systems and completing machine testing, the multifunctional roller coaster track detection robot exhibits outstanding performance in track appearance, thickness and crack detection. This study provides great potential for intelligent detection in amusement equipment, railcar, train and so on. Full article

The cleaning and maintenance of large-scale façades is a high-risk industry. Although existing wall-climbing robots can replace humans who work on façade surfaces, it is difficult for them to operate on façade protrusions due to a lack of perception of the surrounding environment. To address this problem, this paper proposes a binocular vision-based method to assist wall-climbing robots in performing autonomous rust removal and painting. The method recognizes façade protrusions through binocular vision, compares the recognition results with an established dimension database to obtain accurate information on the protrusions and then obtains parameters from the process database to guide the operation. Finally, the robot inspects the operation results and dynamically adjusts the process parameters according to the finished results, realizing closed-loop feedback for intelligent operation. The experimental results show that the You Only Look Once version 5 (YOLOv5) recognition algorithm achieves a 99.63% accuracy for façade protrusion recognition and a 93.33% accuracy for the detection of the rust removal effect using the histogram comparison method. The absolute error of the canny edge detection algorithm is less than 3 mm and the average relative error is less than 2%. This paper establishes a vision-based façade operation process with good inspection effect, which provides an effective vision solution for the automation operation of wall-climbing robots on the façade. Full article

The coal mine wind shaft is an important ventilation channel in coal mines, and it is of great significance to ensure its long-term safety. At present, the inspection of wind shafts still depends on manual work, which has low reliability and high risk. There are two main problems in the shaft wall detection of ventilation shafts: (1) The humidity and dust concentration in ventilation shafts are high, which makes imaging difficult; (2) the cracks on the shaft wall are long and irregular, so it is impossible to acquire the information of the whole crack from a single photo. Firstly, the mapping analysis between the concentration of water vapor and dust in the wind shaft and the image definition is determined by experiments. Then, the inspection robot is designed to move along the axial and circumferential directions to get close to the shaft wall, and the rack-and-rail drive design is adopted to ensure the real-time position feedback of the robot. Then, through the crack parameter detection method based on depth learning, the movement direction of the robot is controlled according to the crack direction so as to ensure that the complete crack parameters are obtained. Finally, the crack detection algorithm is verified by experiments. Full article

The internal inspection of corrosion in large natural gas pipelines is a fundamental task for the prevention of possible failures. Photos and videos provide direct proof of internal corrosion defects. However, the implementation of this technique is limited by fast robot motion and poor lighting conditions, with high-quality images being key to its success. In this work, we developed a natural gas-driven pipeline endoscopic robot (GDPER) for the visual inspection of the inner wall surfaces of pipelines. GDPER consists of driving, odometer, and vision modules connected by universal joints. It is designed to work in a 154 mm gas-pressurized pipeline up to a maximum of 6 MPa, allowing it to smoothly pass through bends and cross-ring welds at a maximum speed of 3 m/s using gas pressure driving. Test results have shown that HD MP4 video files can be obtained, and the location of defects on the pipelines can be detected by intelligent video image post-processing. The gas-driven function enables the survey of very long pipelines without impacting the transport of the pipage. Full article

Wall-climbing robots have been well-developed for storage tank inspection. This work presents a backstepping sliding-mode control (BSMC) strategy for the spatial trajectory tracking control of a wall-climbing robot, which is specially designed to inspect inside and outside of cylindrical storage tanks. The inspection robot is designed with four magnetic wheels, which are driven by two DC motors. In order to achieve an accurate spatial position of the robot, a multisensor-data-fusion positioning method is developed. The new control method is proposed with kinematics based on a cylindrical coordinate system as the robot is moving on a cylindrical surface. The main purpose is to promote a smooth and stable tracking performance during inspection tasks, under the consideration of the robot’s kinematic constraints and the magnetic restrictions of the adhesion system. The simulation results indicate that the proposed sliding mode controller can quickly correct the errors and global asymptotic stability is achieved. The prototype experimental results further validate the advancement of the proposed method; the wall-climbing robot can track both longitudinal and horizontal spatial trajectories stably with high precision. Full article

An accurate estimation of pipe attributes, pose of pipeline inspection gauge (PIG), and downstream pipeline topology is essential for successful in-line inspection (ILI) of underground compressible gas pipelines. Taking a 3D point cloud of light detection and ranging (LiDAR) or time-of-flight (ToF) camera as the input, in this paper, we present the simultaneous pipe-attribute and PIG-pose estimation (SPPE) approach that estimates the optimal pipe-attribute and PIG-pose parameters to transform a 3D point cloud onto the inner pipe wall surface: major- and minor-axis lengths, roll, pitch, and yaw angles, and 2D deviation from the center of the pipe. Since the 3D point cloud has all spatial information of the inner pipe wall measurements, this estimation problem can be modeled by an optimal transformation matrix estimation problem from a PIG sensor frame to the global pipe frame. The basic idea of our SPPE approach is to decompose this transformation into two sub-transformations: The first transformation is formulated as a non-linear optimization problem whose solution is iteratively updated by the Levenberg–Marquardt algorithm (LMA). The second transformation utilizes the gravity vector to calculate the ovality angle between the geometric and navigation pipe frames. The extensive simulation results from our PIG simulator based on the robot operating system (ROS) platform demonstrate that the proposed SPPE can estimate the pipe attributes and PIG pose with excellent accuracy and is also applicable to real-time and post-processing non-destructive testing (NDT) applications thanks to its high computational efficiency. Full article