Mechatronic Systems Research Articles

Lightweight mechatronic system for humanoid robot

Abstract This paper presents the technical specifications of a lightweight humanoid robot platform named Robinion Sr. including its mechanical and electrical design. We describe a versatile and robust mechatronic system, efficient walking gait, and software architecture of the humanoid robot. The humanoid robot platform is targeted for use in a range of applications, including research and development, competitions, and the service industry. A reduced platform cost was an essential consideration in our design. We introduce a specialized and inexpensive mechanical design, which includes a parallel-kinematics leg design, external gears, and low-cost controllers and sensors. The humanoid robot is equipped with an efficient electronic structure and a tablet computer for task scheduling, control, and perception, as well as an embedded controller for solving forward & inverse kinematics and low-level actuator control. The perception system recognizes objects at real-time inference with Deep Learning-based detection algorithms without a dedicated GPU. We present and evaluate the capabilities of our newly developed advanced humanoid robot and believe it is a suitable platform for the academic and industrial robotics community.

Condition Monitoring using Domain-Adversarial Networks with Convolutional Kernel Features

The data-based condition monitoring and diagnosis of a mechatronic system can be a challenge due to the amount of labeled data traditional methods require. Moreover, transferring a trained classification model from its source domain to another mechatronic system is a difficult task due to even minor differences between sensors, dimensions, or environmental conditions. Additionally, labeled data may not be available or difficult to obtain in this new target domain. In this paper, a novel approach to time series based domain adaptation is proposed by modifying a Domain-Adversarial Neural Network. Therefore, a MiniRocket transform is combined with an artificial neural network as a composed feature extractor. This model aims to extract domain invariant features from multivariate time series data that can be used for cross-domain condition monitoring of mechatronic systems. The model is tested for belt tension monitoring using data from two belt drives considering two types of excitation. Experimental results for wideband excitation show that the proposed model estimates the tension of the belt with high accuracy in the target domain (unsupervised). For the jerk-limited excitation, accuracy is improved for the target domain in a semi-supervised setting.

Reliability prediction of a mechatronic hydraulic drive at the early design stages

The article deals with the reliability of technological machines that use hydraulic feed drives. A priority task in mechanical engineering is the design of mechanical systems with higher stability, reliability, and performance. Various mechatronic systems are used to solve this problem, including mechatronic motion modules for hydraulic drives of technological machines. It is noted that the study of the reliability of mechatronic systems presents a special problem since the interaction of mechanical, hydraulic, and electronic systems gives rise to some new aspects of the theory of reliability. The main technical solutions for reliability incorporated in the design directly impact the machine's functional and economic characteristics. When predicting reliability at an early stage of design, there is the greatest uncertainty (entropy) in assessing the possible states of the machine. As an object of study, a mechatronic hydraulic drive is considered an electro-hydraulic motion module, which can be used in feed drives for heavy metal-cutting machines or industrial robots with a large load capacity. An important parametric characteristic of such a drive is the positioning accuracy of the working body, its stability, and the preservation of values within the specified limits over time. A review of the methodology for assessing and predicting the reliability of mechanical systems is carried out. It is noted that several statistical methods require the accumulation of test results for serial models or prototypes, but many important factors may not be taken into account. The purpose of this article is to obtain the results of predicting the parametric reliability of mechatronic hydraulic drives by using the method of expert assessments (rank correlation) at the early stages of design. This method is based on the ability of independent experts (qualified experts in the field) to provide useful information in the face of quantitative uncertainty. When setting the problem of predicting reliability, the factors that affect the positioning accuracy of the hydraulic drive were ranked in order of importance (ranked). An analytical relationship was established between the weight of the factor and its number in the series. The arithmetic mean weight, the mean relative weight, the standard deviation of the factors that affect the parametric reliability of the drive, and the coefficient of variation are determined. The consistency of expert opinions was shown based on heuristic indicators using the concordance coefficient (Kendall criterion). The considered technique can be used to predict and evaluate the reliability of mechatronic systems that are being developed for use in various fields of technology.

Feasibility of Controlling the Motion of Industrial Robots, CNC Machine Tools, and Mechatronic Systems. Part 1

Feasibility of Controlling the Motion of Industrial Robots, CNC Machine Tools, and Mechatronic Systems. Part 1

Autoencoder-Based Iterative Modeling and Multivariate Time-Series Subsequence Clustering Algorithm

This paper introduces an algorithm for the detection of change-points and the identification of the corresponding subsequences in transient multivariate time-series data (MTSD). The analysis of such data has become increasingly important due to growing availability in many industrial fields. Labeling, sorting or filtering highly transient measurement data for training Condition-based Maintenance (CbM) models is cumbersome and error-prone. For some applications it can be sufficient to filter measurements by simple thresholds or finding change-points based on changes in mean value and variation. But a robust diagnosis of a component within a component group for example, which has a complex non-linear correlation between multiple sensor values, a simple approach would not be feasible. No meaningful and coherent measurement data, which could be used for training a CbM model, would emerge. Therefore, we introduce an algorithm that uses a recurrent neural network (RNN) based Autoencoder (AE) which is iteratively trained on incoming data. The scoring function uses the reconstruction error and latent space information. A model of the identified subsequence is saved and used for recognition of repeating subsequences as well as fast offline clustering. For evaluation, we propose a new similarity measure based on the curvature for a more intuitive time-series subsequence clustering metric. A comparison with seven other state-of-the-art algorithms and eight datasets shows the capability and the increased performance of our algorithm to cluster MTSD online and offline in conjunction with mechatronic systems.

Adaptive Robust Fault-Tolerant Regulation of Mechatronic Systems with Prescribed-Time Convergence

In this paper, we propose a synchronized prescribed-time control strategy for a class of nonlinear mechatronic systems with external disturbance, actuation saturation, and actuator faults, which features simultaneous translational and rotational motion tracking in the same prescribed time. Dual quaternion is employed to model the coupling effect between translational and rotational motions, which provides a unified representation for describing multiple degree-of-freedom motions. In addition, online adaptive technology is incorporated for real-time monitoring and separation of actuator failure information. The adaptive capability of the controller to parameter perturbation, disturbance, and fault deviation is therefore enhanced. Furthermore, the closed-loop system is featured by L2 gain stability/robustness against thrust output deviation, while the system trajectory is guaranteed to converge with user-defined settling time. Finally, numerical simulations on a microsatellite platform with redundant thrusters are performed to verify the effectiveness of the proposed fault-tolerant control approach.

Cascaded Calibration of Mechatronic Systems via Bayesian Inference

Sensors in high-precision mechatronic systems require accurate calibration, which is achieved using test beds that, in turn, require even more accurate calibration. The aim of this paper is to develop a cascaded calibration method for position sensors of mechatronic systems while taking into account the variance of the calibration model of the test bed. The developed calibration method employs Gaussian Process regression to obtain a model of the position-dependent sensor inaccuracies by combining prior knowledge of the sensor with data using Bayesian inference. Monte Carlo simulations show that the developed calibration approach leads to significantly higher calibration accuracy when compared to alternative regression techniques, especially when the number of available calibration points is limited. The results indicate that more accurate calibration of position sensors is possible with fewer resources.

A method for optimizing product architectures for the management of disturbance factors

The demand for a better product and process quality is ever increasing in the globalized world. To satisfy this demand the management of disturbance factors in mechatronic systems is essential. The applicability and efficiency of strategies targeted at the management of these factors depend on the components, the source of the disturbance factors and the systems building structure. Therefore, a method is developed to derive a building structure of a system, which supports the management of disturbance factors, from an existing functional structure. This support lowers the effort, necessary to manage disturbance factors, and thereby aids in increasing the quality of the product and the associated process. Finally, the presented method is applied on to a sensor integrating timing belt to demonstrate its usability and practicality.

Mechatronic gripper system and delivery platform for the autonomous cargo transport with unmanned aerial vehicles

For intralogistics material transport with unmanned aerial vehicles (UAVs), special pickup and release devices are necessary to guarantee a reliable and efficient transport process in the field of application. Therefore, the paper presents a process-reliable transport system comprising a mechatronic gripper and a landing platform to conduct autonomous cargo pick-up and delivery. The presented configuration was used with a commercial UAV for the autonomous product handover between defined locations. To compare the performance against conventional methods of transporting small goods, different scenarios were carried out. The potential time saving is verified through comparisons with conventional conveyor systems. The cooperation of drone fleets and multi-UAV monitoring by a single operator are also discussed.

Settling Time Optimization in Wire Bonder Systems via Extremum-Seeking Control1

Adequate tuning of control laws is essential for high positioning accuracy, large system throughput, and reliability in high-end mechatronic and robotic systems. However, a population of such systems generally shows slight variations in dynamic responses due to, e.g., manufacturing tolerances, different disturbance situations, or position-dependent dynamics. Given the time-consuming nature of controller design, even by experienced control engineers, typically just one control law is designed for the whole system population based on worst-case bounds on variations in dynamic responses, resulting in a loss of individual system performance. The main contribution of this paper is the development of an automated controller tuning approach, based on extremum-seeking control, for settling time optimization via individual controller tuning. While other automated controller tuning methods exist, the developed approach allows inclusion of closed-loop stability and robustness constraints based solely on non-parametric frequency-response measurements of open-loop plant dynamics, and therewith directly optimizes transient system performance in a purely data-based manner. The proposed approach has been applied in simulation in an industrial case study for settling time optimization in point-to-point motions of a wire bonder system. In this case study, the effectiveness of the approach has been shown by achieving significant performance increases of 39.4% and 40.6% compared to controllers designed by experienced control engineers using manual loop-shaping techniques and a frequency-based auto-tuner, respectively, without needing manual tuning effort.

Category theory-based collaborative design methodology for mechatronic systems

Recent advances in companies are characterized by highly dynamic, knowledge-intensive and collaborative process. This has become primary concern for mechatronic systems since they involve multiple disciplines and knowledge. This requires a close exchange in order to share knowledge between the different design teams. The first step in knowledge sharing is to identify the most important knowledge that need to be capitalized, which we call “crucial knowledge”. During this exchange, heterogeneous knowledge and modelling languages are involved in the design process, which can lead to conflicts. Hence, the challenge is to continuously capture and handle such conflicts between expert models. Thus, the focus of this paper is to propose a new collaborative design model suitable for mechatronic concurrent design. Our contribution lies in identifying crucial knowledge and resolving conflicts in a formal way in order to ensure efficient collaboration. Our methodology called Category Theory-based Collaborative Design (CaTCoD) is described with its associated meta-model. A demonstrator is also used to validate the proposed methodology using an example from the aeronautic field.

Upgradeable Mechatronic Systems - An Approach to determine changing Product Properties using Foresight

In light of the increasing complexity and dynamic of the market environment, there is a need to consider future requirements during the development of upcoming product generations. This applies in particular to modular product architectures as their elements are used in several products and over a longer period. To overcome this challenge and to develop more sustainable products, upgrading can be a solution. Based on identified options for action, this paper proposes an approach to determine changing product properties based on the Model of PGE – Product Generation Engineering. Depending on the potential of the individual characteristics of a product property in its future environment, the properties can be classified as static or dynamic time-dependent for later upgrade planning. The approach was applied in a case study and a research project. Its applicability and usability could be demonstrated. Results from the application of the approach can be used in development projects to define upgrade packages for the upcoming product generation or to optimize the modularization of future products.

A novel magnetically levitated tip/tilt motion platform

This paper presents the mechatronic system design and control of a tip/tilt motion platform with a magnetically levitated mover tailored for dynamic rotational scanning operation. It employs a Lorentz force-based actuation system with five degrees of freedom and four spherical Halbach arrays on a fully passive mover. The system includes highly integrated optical proximity sensors for sensing the mover position in all degrees of freedom and a passive magnetic bearing for restraining the non-actuated degree of freedom. The actuation system enables a mechanical angular range of ±1° in both axes, with first structural modes of the 3D printed mover occurring at 1 kHz. A control system is designed for the five actively controlled degrees of freedom for obtaining a robustly stable and precise motion system. The resulting closed-loop system has a bandwidth of 200 Hz in the rotational and 100 Hz in the translational degrees of freedom and a small positioning uncertainty of 0.02% of the full motion range.

Model of field robot manipulators and sensor for measuring angular displacement of its rotating parts

This research aims to measure and control the angular change of rotation mechanisms of (energy-saving) robotic manipulators used in agriculture to develop digital farming, energy saving, and quality product harvesting. The novelty of this research is that different processes and images are placed in a special processor for processing, and this robot processes the image according to the size of the tomato plant and tomato and tries to harvest the crop. This study presents the electromagnetic angular displacement sensor and its technical characteristics. The existing electromagnetic angular displacement sensors have been thoroughly analyzed and compared with other types of sensors. The reason for the low sensitivity of the electromagnetic angular displacement sensor has been investigated, and some technical modification to the existing sensor has been made. The magnetic circuits of the electromagnetic sensors have been analyzed. A method is proposed for expanding the range of angular measurements up to 180 degrees and increasing the sensitivity of the electromagnetic sensor without compromising the measurement accuracy. This, in turn, allows high-precision control and measurement of rotating mechanisms of all types of mechatronic systems and agricultural robots.

Models of dynamics of complex heterostructures under pulsed force effects

Relevance is due to insufficient knowledge and development of models of dynamics of complex heterostructures. Modern mechatronic systems include hybrid components consisting of complex heterogeneous structures: mechanical, electrical, electronic, etc. Heterostructures function in extreme conditions due to kinematic, dynamic, temperature, vibration and other external factors and are exposed to external influences. To create a reliable system for protecting complex heterostructures, it is necessary to build appropriate mathematical models that allow you to adequately describe the processes occurring in complex heterostructures. The purpose of the work is to study and develop heterostructural models based on the equations of point dynamics, plate and multilayer structures under the action of force and impulse loads in the presence or absence of internal friction in heterostructures. Particular attention is paid to the study of models of heterostructures with dissipation, with many degrees of freedom under the action of impulse loads.

Технологии и технические средства рекультивации залежных земель с регулированием уровня увлажненности почвы

An assessment of the technological feasibility of the tasks of involving fallow lands in agricultural circulation and increasing the fertility of agricultural land in the long-term period of economic activity is given. Insufficient information content of the use of yield maps for assessing the fertility of fields has been revealed. It is proposed to use maps of the relief of fields, which will allow establishing the dynamics of violation of the water-air regime of the soil. It is substantiated that in the process of involving fallow lands into circulation, it is required to introduce a technological operation of micro topographic analysis of the degree of soil moisture. An algorithm for switching on the field leveling operation (surface leveling of the field plane) using modern positioning systems has been developed. It was revealed that leveling the field with a laser level made it possible to reduce yield fluctuations by 20% within the cultivated area of the field and increase yield by 25‑30% (an example of sowing corn). Shortcomings of positioning accuracy with the use of laser and satellite positioning have been established. It is proposed to transfer digital information transmission modules to network clusters with the choice of the best digital data transmission channel by including an uninterrupted positioning module with digital data transmission over a 434 MHz and 864 MHz radio channel with a range of up to 600 meters to other digital information transmission modules of the vehicle positioning. A plan for the implementation of the concept of forming a digital field on the basis of a field experimental station of the RSAU-MAA named after C.A. Timiryazev, with the aim of creating a frontier for the sustainable development of closed life cycle technologies through the introduction of innovations using the multiplicative interaction of mechatronic systems and telematics for agro-industrial complex equipment

Automated Design Exploration and Dynamic Safety Analysis for Optimization of Mechatronic Systems in Safety-Critical Automotive Applications

Automated Design Exploration and Dynamic Safety Analysis for Optimization of Mechatronic Systems in Safety-Critical Automotive Applications

Design and Control of a Tara Flour Processing Machine in Ayacucho – Peru, 2023

This article proposes the design and control of a Tara flour processing machine with the aim of increasing profitability and reducing the time required for its processing. The research presents a mechatronic system composed of two main systems: one mechanical and the other electrical-electronic. The mechanical system consists of three parts. In the first part, the feeding and dosing is carried out, where the Tara is filled and shelled. In the second part, there is the shaking process, which consists of separating the seeds from the shell. The third part refers to the grinding of the Tara, thus obtaining the final product: flour. The electric-electronic system incorporates an AtMega 328P microcontroller to regulate the speeds of the motors based on the readings of the sensors used for proper processing. The implementation of this project would reduce the production time of Tara flour in the city of Ayacucho by 75% compared to the traditional method. This demonstrates the possibility of improving the production process of Tara flour.

Smart angular displacement sensor for agricultural field robot manipulators

This study presents the electromagnetic angular displacement sensor and its technical characteristics. The existing electromagnetic angular displacement sensors have been thoroughly analyzed and compared with other types of sensors. The reason for the low sensitivity of the electromagnetic angular displacement sensor has been investigated and some technical modification to the existing sensor has been made. The magnetic circuits of the electromagnetic sensors have been analyzed. A method is proposed for expanding the range of angular measurements up to 180 degrees and increasing the sensitivity of the electromagnetic sensor without compromising the measurement accuracy. This, in turn, allows high-precision control and measurement of rotating mechanisms of all types of mechatronic systems and agricultural robots.

Mechatronic Coupling System for Cooperative Manufacturing with Industrial Robots

Rising product variants and shortened product life cycles require more flexible and universally utilizable production systems and machines. Consequently, it can be expected that the importance of industrial robots in production will continuously increase, due to their suitability to take over the role of a universal production machine. However, robots are not yet able to fulfill this role. Industrial use of robots has so far been limited mainly to simple transport and handling tasks in the context of human-robot collaboration as well as highly repetitive automated tasks in the context of manufacturing and assembly. For universal use, robots must be capable to perform more demanding tasks in manufacturing with higher requirements on mechanical stiffness and accuracy. Therefore, this paper presents a mechatronic system to couple two robots to a parallel kinematic system to temporarily increase the mechanical stiffness. The coupled state of the robots allows load sharing, higher process forces and eventually higher precision. The overall goal is to enable robots to perform more demanding manufacturing tasks and thus to be utilized in a wider range of applications. Design requirements, the development approach and optimization methods of the first coupling module prototype will be presented and discussed. The next development steps, a future demonstration system and possible use cases for the coupling module will be shown in the outlook.