This paper presents a robust nonlinear control strategy for a laser scanner’s actuator operating under stochastic mechanical disturbances. External perturbations are represented as bounded stochastic torque inputs, capturing the aggregate effect of structural imbalance, impacts, or system degradation. Experimental observations of vibration-induced angular fluctuations motivate this modeling choice, highlighting the need for control strategies tolerant to bounded stochastic disturbances resulting from unpredictable mechanical faults. A smooth hyperbolic-based control law is proposed to achieve robust velocity tracking under these uncertain conditions. Global asymptotic stability is formally established through Lyapunov analysis, and simulation results confirm that the proposed method effectively maintains convergence and bounded control effort in the presence of estimated disturbance torque. The formulation is suitable for fault-tolerant control of precision actuators where physical irregularities are difficult to isolate or diagnose in real time.

Autonomous mobile robots are essential in industry, logistics, and service applications, such as infrastructure inspection, where navigation in dark and narrow environments is one of the most challenging tasks. This project presents the design and development of a patented artificial vision system for a mobile robot, which combines a high-precision laser scanner and a stereo-vision system. The objective is to enhance the robot’s surface scanning capabilities in complex environments. The proposed methodology allows to determine the relative position between systems to integrate data of the laser scanner with stereo-vision cameras and inertial sensors , providing robust and accurate environmental perception that enables the characterization of ventilation ducts surface. Experimental results show a mean correspondence error of 7 . 4515 mm in absolute terms for the combined data.

To achieve successful autonomous navigation, a vision system that provides continuous and precise three-dimensional data of the system’s surroundings is always needed. An indispensable step in the acquisition of reliable data is the calibration of the system, preferably with a time-efficient and low-complexity approach. In this paper, a robust and efficient calibration method is proposed for the information fusion of a stereo vision system and a Technical Vision System. The proposed methodology achieves an error of xe= 6.9401 mm, ye= 8.0997 mm and ze= 15.1822 mm in 3.0202 seconds of processing time, as proven through experimental results.

This work analyzes the challenges associated with implementing Industry 4.0 in a border region between the United States and Mexico. It addresses economic, technological, educational, and social factors that affect the adoption of advanced manufacturing technologies, including Industrial Electronics. Additionally, it explores potential strategies to mitigate these challenges in a binational context, considering the particularities of the digitization and interconnection of factories that are fundamental to Industry 4.0. The research includes a special analysis of the situation in the Mexican border state of Baja California, providing preliminary findings and insights that can inform further investigation and implementation efforts. Furthermore, this study examines the integration of Industry 4.0 and Industrial Electronics concepts into higher education, highlighting the role of universities in preparing students with the necessary skills to thrive in a modern industrial landscape.

This study presents a robust control strategy to mitigate the effects of friction and mechanical vibrations in a 1-DOF electromechanical actuator for laser scanning systems. Using hyperbolic tangent functions ensures bounded control signals, preventing actuator saturation. Real-time vibration measurements with MPU6050 modules were conducted to characterize the system’s mechanical behavior. The stability of the system is ana-lyzed using the direct Lyapunov method and Barbalat’s lemma, ensuring global asymptotic stability. Simulations demonstrated the control strategy’s effectiveness in improving stability and accuracy. Future work will focus on implementing this control in a physical prototype for validation.

non-contact 3D spatial coordinate measurement systems, based on optical laser scanning as technical vision systems (TVS) for signal processing, are essential methodologies for obtaining topographies in high-risk environments where human exploration is limited. However, these systems have limitations in resolution, particularly when addressing features such as surface texture and small curvatures at edges. Therefore, in this work, we propose the implementation of speckle pattern projection as a complementary innovative solution. Supported by the digital image correlation (DIC) methodology and the use of multivariate methods such as principal component analysis (PCA), we obtain results from different wall surfaces in a pipe prototype. Additionally, we analyze the behavior of the signal received by the 3D scanner sensor, which provides complementary information about the study surface. This demonstrates that the combination of speckle pattern projection and three-dimensional laser scanning is an additional tool for advanced detection of substance material during pipeline monitoring.

This work presents improvements to a patented 3D laser scanning system with a friction-compensated laser positioning mechanism. By employing a dynamic friction model, the system accurately identifies angular positioning errors through a combination of manual and automatic measurements with different control inputs. The study conducts experiments involving multiple friction cycles and SEM micrograph analysis to compare the microscopic irregularities of steel surfaces before and after friction-based positioning. Parameters of the friction system are derived or estimated from processed input-output test data. A nonlinear control is proposed to compensate for friction effects, resulting in improved positioning accuracy. Experimental implementation using an STM32 board demonstrates a remarkable reduction in the uncertainty of 3D coordinates measured by applying friction-compensated laser positioning. The findings highlight the effectiveness of the proposed friction compensation method, making the 3D laser scanning system more precise and reliable for diverse applications.

Laser Scanners used for Structural Health Monitoring applications such as Pipelines Structural Inspections normally needs Point Clouds from a large quantity of individual measurements that should be adjusted or post-processed to decrease overall point-cloud errors depending on scanner's characteristics. The posterior adjustment is commonly addressed by different mathematical methods or computational algorithms. According to application requirements methods such as machine learning, signal filtering, or RANSAC algorithms are used. This paper shows the application of an adapted/modify RANSAC algorithm especially suited for the pipeline inspection task. Aiming to increase the percentage of useful data per capture.

Friction is one of the significant factors to degrade the transient accuracy of positioning systems. In this respect, the present paper proposes implementing a nonlinear control to perform friction compensation to improve the positioning accuracy for a controlled DC motor of a laser positioning system with friction, which is assumed to be appropriately described using a dynamic friction model. The global asymptotic positioning stability proof was performed using Lyapunov’s direct method.