Modeling, Sensor Fusion and Control Techniques in Applied Robotics

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Robotics, Mechatronics and Intelligent Machines".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 46303

Special Issue Editors


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Guest Editor
1. Institute of Information Technology, University of Dunaujvaros, Tancsics M. Str. 1/A, H-2401 Dunaujvaros, Hungary
2. Symbolic Methods in Material Analysis and Tomography Research Group, Faculty of Engineering and Information Technology, University of Pecs, Boszorkany Str. 6, H-7624 Pecs, Hungary
Interests: robotics; fuzzy control; electrical engineering; optimization methods; electrical impedance tomography; control theory
Special Issues, Collections and Topics in MDPI journals
Institute of Informatics, University of Dunaújváros, 2400 Dunaújváros, Hungary
Interests: kalman filter; attitude estimation; fuzzy control; fuzzy Logic; robotics; control; inertial measurement unit; imu; MARG; inverted pendulum; adaptive filter; sensor fusion
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Faculty of Mechanical Engineering, Lodz University of Technology, 90-924 Łódź, Poland
Interests: nonlinear dynamics; non-linear mechanics; control; biomechanics; mechatronics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The realization of precise, robust, and intelligent control solutions is based on multiple coordinated design steps in modern robot systems. These design steps include (i) the concrete realization of task-oriented mechatronics systems, (ii) both the derivation and validation of realistic mathematical models, (iii) the calibration of the applied sensor networks, (iv) the estimation of robot states and parameters, and (v) both the design and implementation of intelligent control solutions that provide an energy efficient and robust performance. This Special Issue aims to present novel efficient techniques, which enable the enhancement of overall closed-loop performances in real robot systems (e.g., in mobile robots, UAVs, and robot manipulators). 

Recent research on the below-listed topics is invited. Review papers are also welcome. 

- Optimized mechanics structures in robotic applications, which enable efficient trajectory tracking and translation motion. The analysis can also be extended to vibration diagnostics-based designs, which aim to reduce the levels and patterns of unwanted signals.

- Novel robot modeling and model validation techniques, which provide both relevant and realistic information of real system states. These techniques include novel simulation models and contribute to the obtainment of reliable deductions connected to the behavior of dynamical systems.

- Fusion algorithms of sensor networks for sampling the robot dynamics. These algorithms can include novel filter structures, sensor calibration techniques, and both robust and reliable state estimation methods. Novel measurement solutions that enable the effective derivation of robot states and parameters can also be proposed.

- Novel energy-efficient control solutions that provide a superior performance compared with the conventional methods. Implementation of robust control approaches that handle both the parameter uncertainties/measurement disturbances, and ensure a satisfying control performance.

- Efficient image processing methods that aim to provide the basis for motion planning and reliable trajectory tracking in robot systems.

- Applied industrial solutions in robot systems, which present complex design, implementation, and test results, e.g., artificial intelligence-, IoT-, soft computing-, and/or Industry 4.0-based intelligent robotic solutions in agriculture, construction, medicine, rehabilitation, and biological research. 

Prof. Dr. Jan Awrejcewicz
Dr. Akos Odry
Dr. Peter Odry
Guest Editors

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Keywords

  • applied robotics
  • robot modeling
  • model validation
  • nonlinear dynamics
  • sensor fusion
  • state estimation
  • sensor calibration
  • robust/adaptive control
  • fuzzy systems
  • servo systems
  • stability problems
  • vibrations

Published Papers (17 papers)

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17 pages, 29192 KiB  
Article
Localization of Mobile Manipulator in Vineyards for Autonomous Task Execution
by Ivan Hrabar and Zdenko Kovačić
Machines 2023, 11(4), 414; https://doi.org/10.3390/machines11040414 - 23 Mar 2023
Cited by 1 | Viewed by 1173
Abstract
Although robotic systems have found their place in agriculture, there are still many challenges, especially in the area of localization in semi-structured environments. A robotic system has been developed and tested to perform various tasks in the steep vineyards of the Mediterranean region. [...] Read more.
Although robotic systems have found their place in agriculture, there are still many challenges, especially in the area of localization in semi-structured environments. A robotic system has been developed and tested to perform various tasks in the steep vineyards of the Mediterranean region. In this paper, we describe a method for vine trunk localization, based solely on the visual recognition of vine trunks by neural networks fed by an RGB camera. Assuming that the height of the first wire in the vineyard is known, the proposed method is used to determine the location of vines in the immediate vicinity of the all-terrain mobile manipulator—ATMM-VIV—needed for spraying and bud suckering. The experiment was conducted in a slightly inclined vineyard to evaluate the proposed localization method. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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24 pages, 5324 KiB  
Article
Fingerprinting-Based Indoor Positioning Using Data Fusion of Different Radiocommunication-Based Technologies
by Dominik Csik, Ákos Odry and Peter Sarcevic
Machines 2023, 11(2), 302; https://doi.org/10.3390/machines11020302 - 17 Feb 2023
Cited by 7 | Viewed by 1630
Abstract
Wireless-radio-communication-based devices are used in more and more places with the spread of Industry 4.0. Localization plays a crucial part in many of these applications. In this paper, a novel radiocommunication-based indoor positioning method is proposed, which applies the fusion of fingerprints extracted [...] Read more.
Wireless-radio-communication-based devices are used in more and more places with the spread of Industry 4.0. Localization plays a crucial part in many of these applications. In this paper, a novel radiocommunication-based indoor positioning method is proposed, which applies the fusion of fingerprints extracted with various technologies to improve the overall efficiency. The aim of the research is to apply the differences, which occur due to that different technologies behave differently in an indoor space. The proposed method was validated using training and test data collected in a laboratory. Four different technologies, namely WiFi received signal strength indication (RSSI), ultra-wideband (UWB) RSSI, UWB time of flight (TOF) and RSSI in 433 MHz frequency band and all of their possible combinations, were tested to examine the performance of the proposed method. Three widely used fingerprinting algorithms, the weighted k-nearest neighbor, the random forest, and the artificial neural network were implemented to evaluate their efficiency with the proposed method. The achieved results show that the accuracy of the localization can be improved by combining different technologies. The combination of the two low-cost technologies, i.e., the WiFi and the 433 MHz technology, resulted in an 11% improvement compared to the more accurate technology, i.e., the 433 MHz technology. Combining the UWB module with other technologies results in a less significant improvement since this sensor provides lower error rates, when used alone. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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18 pages, 4070 KiB  
Article
Potential Field Control of a Redundant Nonholonomic Mobile Manipulator with Corridor-Constrained Base Motion
by Jakob Baumgartner, Tadej Petrič and Gregor Klančar
Machines 2023, 11(2), 293; https://doi.org/10.3390/machines11020293 - 16 Feb 2023
Cited by 2 | Viewed by 2689
Abstract
This work proposes a solution for redundant nonholonomic mobile manipulator control with corridor constraints on base motion. The proposed control strategy applies an artificial potential field for base navigation to achieve joint control with desired trajectory tracking of the end effector. The overall [...] Read more.
This work proposes a solution for redundant nonholonomic mobile manipulator control with corridor constraints on base motion. The proposed control strategy applies an artificial potential field for base navigation to achieve joint control with desired trajectory tracking of the end effector. The overall kinematic model is created by describing the nonholonomic mobile platform and the kinematics of the manipulator. The objective function used consists of a primary control task that optimizes the joint variables to achieve the desired pose or trajectory of the end effector and a secondary control task that optimizes the joint variables for the base to support the arm and stay within the corridor. As a last priority, an additional optimization is introduced to optimize the maneuverability index. The proposed baseline navigation has global convergence without local minima and is computationally efficient. This is achieved by an optimal grid-based search on a coarse discrete grid and a bilinear interpolation to obtain a continuous potential function and its gradient. The performance of the proposed control algorithm is illustrated by several simulations of a mobile manipulator model derived for a Pal Tiago mobile base and an Emiko Franka Panda robotic manipulator. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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19 pages, 2707 KiB  
Article
Observer-Based Robust Fuzzy Controller Design for Uncertain Singular Fuzzy Systems Subject to Passivity Criterion
by Wen-Jer Chang, Yu-Min Huang, Cheung-Chieh Ku and Jialu Du
Machines 2023, 11(2), 280; https://doi.org/10.3390/machines11020280 - 13 Feb 2023
Cited by 5 | Viewed by 1132
Abstract
This paper discusses an observer-based control problem for uncertain Takagi–Sugeno Fuzzy Singular Systems (T-SFSS) subject to passivity performance constraints. Through the Parallel Distributed Compensation (PDC) approach and the Proportional Derivative (PD) control scheme, an observer-based fuzzy controller is constructed to achieve the stability [...] Read more.
This paper discusses an observer-based control problem for uncertain Takagi–Sugeno Fuzzy Singular Systems (T-SFSS) subject to passivity performance constraints. Through the Parallel Distributed Compensation (PDC) approach and the Proportional Derivative (PD) control scheme, an observer-based fuzzy controller is constructed to achieve the stability of the considered system. An unlimited positive definite matrix is utilized to construct the Lyapunov function and derive sufficient stability conditions to develop a relaxed design method. Moreover, some technologies, such as the Schur complement, projection lemma, and Singular Value Decomposition (SVD), are applied to convert the conditions to Linear Matrix Inequality (LMI) form. Therefore, the convex optimization algorithm is used to solve the LMI conditions to find feasible solutions. The observer-based fuzzy controller is established with the obtained solutions to guarantee stability and passivity performance for the uncertain nonlinear singular systems. Finally, two examples are provided to verify the availability of the proposed fuzzy control approach. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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20 pages, 2687 KiB  
Article
Window Shape Estimation for Glass Façade-Cleaning Robot
by Takuma Nemoto, Shunsuke Nansai, Shohei Iizuka, Masami Iwase and Hiroshi Itoh
Machines 2023, 11(2), 175; https://doi.org/10.3390/machines11020175 - 27 Jan 2023
Viewed by 1979
Abstract
This paper presents an approach to the estimation of a window shape for increasing the adaptability of glass façade-cleaning robots to different buildings. For this approach, a window scanning robot equipped with a 2D laser range scanner installed perpendicularly to a window surface [...] Read more.
This paper presents an approach to the estimation of a window shape for increasing the adaptability of glass façade-cleaning robots to different buildings. For this approach, a window scanning robot equipped with a 2D laser range scanner installed perpendicularly to a window surface is developed for the testbed, and a method for the window shape estimation is proposed, which consists of the robot’s pose estimation with an extended Kalman filter (EKF) and the loop closure based on the robot’s pose estimated. The effectiveness of the proposed approach is demonstrated through an experiment that is carried out on a window placed on a floor. The experimental results show that the window scanning robot can acquire a window shape, moving on a window surface, and the proposed approach is effective in increasing the accuracy of the window shape estimation. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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19 pages, 2537 KiB  
Article
On the Use of a Genetic Algorithm for Determining Ho–Cook Coefficients in Continuous Path Planning of Industrial Robotic Manipulators
by Teodor Grenko, Sandi Baressi Šegota, Nikola Anđelić, Ivan Lorencin, Daniel Štifanić, Jelena Štifanić, Matko Glučina, Borna Franović and Zlatan Car
Machines 2023, 11(2), 167; https://doi.org/10.3390/machines11020167 - 25 Jan 2023
Cited by 2 | Viewed by 1572
Abstract
Path planning is one of the key steps in the application of industrial robotic manipulators. The process of determining trajectories can be time-intensive and mathematically complex, which raises the complexity and error proneness of this task. For these reasons, the authors tested the [...] Read more.
Path planning is one of the key steps in the application of industrial robotic manipulators. The process of determining trajectories can be time-intensive and mathematically complex, which raises the complexity and error proneness of this task. For these reasons, the authors tested the application of a genetic algorithm (GA) on the problem of continuous path planning based on the Ho–Cook method. The generation of trajectories was optimized with regard to the distance between individual segments. A boundary condition was set regarding the minimal values that the trajectory parameters can be set in order to avoid stationary solutions. Any distances between segments introduced by this condition were addressed with Bezier spline interpolation applied between evolved segments. The developed algorithm was shown to generate trajectories and can easily be applied for the further path planning of various robotic manipulators, which indicates great promise for the use of such algorithms. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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35 pages, 4044 KiB  
Article
Classification of Wall Following Robot Movements Using Genetic Programming Symbolic Classifier
by Nikola Anđelić, Sandi Baressi Šegota, Matko Glučina and Ivan Lorencin
Machines 2023, 11(1), 105; https://doi.org/10.3390/machines11010105 - 12 Jan 2023
Cited by 3 | Viewed by 1536
Abstract
The navigation of mobile robots throughout the surrounding environment without collisions is one of the mandatory behaviors in the field of mobile robotics. The movement of the robot through its surrounding environment is achieved using sensors and a control system. The application of [...] Read more.
The navigation of mobile robots throughout the surrounding environment without collisions is one of the mandatory behaviors in the field of mobile robotics. The movement of the robot through its surrounding environment is achieved using sensors and a control system. The application of artificial intelligence could potentially predict the possible movement of a mobile robot if a robot encounters potential obstacles. The data used in this paper is obtained from a wall-following robot that navigates through the room following the wall in a clockwise direction with the use of 24 ultrasound sensors. The idea of this paper is to apply genetic programming symbolic classifier (GPSC) with random hyperparameter search and 5-fold cross-validation to investigate if these methods could classify the movement in the correct category (move forward, slight right turn, sharp right turn, and slight left turn) with high accuracy. Since the original dataset is imbalanced, oversampling methods (ADASYN, SMOTE, and BorderlineSMOTE) were applied to achieve the balance between class samples. These over-sampled dataset variations were used to train the GPSC algorithm with a random hyperparameter search and 5-fold cross-validation. The mean and standard deviation of accuracy (ACC), the area under the receiver operating characteristic (AUC), precision, recall, and F1score values were used to measure the classification performance of the obtained symbolic expressions. The investigation showed that the best symbolic expressions were obtained on a dataset balanced with the BorderlineSMOTE method with ACC¯±SD(ACC), AUC¯macro±SD(AUC), Precision¯macro±SD(Precision), Recall¯macro±SD(Recall), and F1score¯macro±SD(F1score) equal to 0.975×1.81×103, 0.997±6.37×104, 0.975±1.82×103, 0.976±1.59×103, and 0.9785±1.74×103, respectively. The final test was to use the set of best symbolic expressions and apply them to the original dataset. In this case the ACC¯±SD(ACC), AUC¯±SD(AUC), Precision¯±SD(Precision), Recall¯±SD(Recall), and F1score¯±SD(F1Score) are equal to 0.956±0.05, 0.9536±0.057, 0.9507±0.0275, 0.9809±0.01, 0.9698±0.00725, respectively. The results of the investigation showed that this simple, non-linearly separable classification task could be solved using the GPSC algorithm with high accuracy. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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25 pages, 7917 KiB  
Article
6-Dimensional Virtual Human-Machine Interaction Force Estimation Algorithm in Astronaut Virtual Training
by Lingjie Lin, Lan Wang, Ying Chang, Lixun Zhang and Feng Xue
Machines 2023, 11(1), 46; https://doi.org/10.3390/machines11010046 - 1 Jan 2023
Cited by 1 | Viewed by 1188
Abstract
It is necessary to conduct virtual training for astronauts on the ground to improve the efficiency and safety of astronauts carrying objects in space. Cooperation between the two astronauts is required when handling massive objects. During this process, it is necessary to obtain [...] Read more.
It is necessary to conduct virtual training for astronauts on the ground to improve the efficiency and safety of astronauts carrying objects in space. Cooperation between the two astronauts is required when handling massive objects. During this process, it is necessary to obtain the operating force of each astronaut. The research purpose of this paper was to propose an algorithm to map the astronaut’s operation on the VR handle to the human–machine interaction force without the robot’s participation, thereby saving costs. In this paper, a virtual robot simulation model is established, while the controller is designed based on the inverse system method. The virtual human–machine interaction force was obtained based on the inverse dynamics method. The influence of different parameters on the final position of the virtual object was analyzed. The physical engine was integrated into the virtual force sensor to ensure that the human–machine interaction forces of multiple astronauts can be coupled. The results showed that the virtual human–machine interaction force is similar to the real one and has a low output noise (approximately 5.5 N). This force can be applied to astronaut collaborative virtual training. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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19 pages, 9637 KiB  
Article
Performance Analysis of a Robust Controller with Neural Network Algorithm for Compliance Tendon–Sheath Actuation Lower Limb Exoskeleton
by Haimin He, Ruru Xi and Youping Gong
Machines 2022, 10(11), 1064; https://doi.org/10.3390/machines10111064 - 11 Nov 2022
Cited by 4 | Viewed by 1407
Abstract
Robotic rehabilitation of the lower limb exoskeleton following neurological injury has proven to be an effective rehabilitation technique. Developing assistive control strategies that achieve rehabilitative movements can increase the potential for the recovery of the motor coordination of the participants. In this paper, [...] Read more.
Robotic rehabilitation of the lower limb exoskeleton following neurological injury has proven to be an effective rehabilitation technique. Developing assistive control strategies that achieve rehabilitative movements can increase the potential for the recovery of the motor coordination of the participants. In this paper, the innovative contributions are to investigate a robust sliding mode controller (SMC) with radials basis function neural network algorithm (RBFNN) compensator for a novel compliance tendon–sheath actuation lower limb exoskeleton (CLLE) to provide intrinsic thigh and shank rehabilitation training. The controller employing the RBFNN compensator is proposed to reduce the impact of friction from the compliance tendon–sheath actuation system (CTSA). In the design of the compensator, a single parameter is investigated to replace the weight information of the neural network. Our proposed controller is shown to yield fast, stable, and accurate control performance regardless of uncertainties interaction. Two additional algorithms, including a robust adaptive sliding mode controller (RASMC) and a sliding mode proportional-integral controller (SMPIC), are introduced in this paper for comparison. The simulations were presented with MATLAB/SIMULINK to validate the superiority of the performance of the proposed controller. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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16 pages, 3240 KiB  
Article
Teaching Motion Control in Mechatronics Education Using an Open Framework Based on the Elevator Model
by Filippo Sanfilippo, Martin Økter, Tine Eie and Morten Ottestad
Machines 2022, 10(10), 945; https://doi.org/10.3390/machines10100945 - 18 Oct 2022
Cited by 3 | Viewed by 2311
Abstract
Universities and other educational institutions may find it difficult to afford the cost of obtaining cutting-edge teaching resources. This study introduces the adoption of a novel open prototyping framework in the context of mechatronics education, employing low-cost commercial off-the-shelf (COTS) components and tools [...] Read more.
Universities and other educational institutions may find it difficult to afford the cost of obtaining cutting-edge teaching resources. This study introduces the adoption of a novel open prototyping framework in the context of mechatronics education, employing low-cost commercial off-the-shelf (COTS) components and tools for the motion control module. The goal of this study is to propose a novel structure for the motion control module in the engineering mechatronics curriculum. The objective is to foster a new teaching method. From a methodology perspective, students are involved in a series of well-organised theoretical lectures as well as practical, very engaging group projects in the lab. To help students understand, draw connections, and broaden their knowledge, the methods of surface learning and deep learning are frequently mixed thoroughly. The structure of the course as well as the key topics are discussed. The proposed open framework, which consists of an elevator model, is presented in details. Students’ early evaluation indicates that the course organisation and subjects are successful and beneficial. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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12 pages, 1328 KiB  
Article
ISVD-Based Advanced Simultaneous Localization and Mapping (SLAM) Algorithm for Mobile Robots
by László Somlyai and Zoltán Vámossy
Machines 2022, 10(7), 519; https://doi.org/10.3390/machines10070519 - 27 Jun 2022
Cited by 4 | Viewed by 1589
Abstract
In the case of simultaneous localization and mapping, route planning and navigation are based on data captured by multiple sensors, including built-in cameras. Nowadays, mobile devices frequently have more than one camera with overlapping fields of view, leading to solutions where depth information [...] Read more.
In the case of simultaneous localization and mapping, route planning and navigation are based on data captured by multiple sensors, including built-in cameras. Nowadays, mobile devices frequently have more than one camera with overlapping fields of view, leading to solutions where depth information can also be gathered along with ordinary RGB color data. Using these RGB-D sensors, two- and three-dimensional point clouds can be recorded from the mobile devices, which provide additional information for localization and mapping. The method of matching point clouds during the movement of the device is essential: reducing noise while having an acceptable processing time is crucial for a real-life application. In this paper, we present a novel ISVD-based method for displacement estimation, using key points detected by SURF and ORB feature detectors. The ISVD algorithm is a fitting procedure based on SVD resolution, which removes outliers from the point clouds to be fitted in several steps. The developed method removes these outlying points in several steps, in each iteration examining the relative error of the point pairs and then progressively reducing the maximum error for the next matching step. An advantage over relevant methods is that this method always gives the same result, as no random steps are included. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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26 pages, 4153 KiB  
Article
Mechanical Design and a Novel Structural Optimization Approach for Hexapod Walking Robots
by Ervin Burkus, Ákos Odry, Jan Awrejcewicz, István Kecskés and Péter Odry
Machines 2022, 10(6), 466; https://doi.org/10.3390/machines10060466 - 11 Jun 2022
Cited by 6 | Viewed by 2384
Abstract
This paper presents a novel model-based structural optimization approach for the efficient electromechanical development of hexapod robots. First, a hexapod-design-related analysis of both optimization objectives and relevant parameters is conducted based on the derived dynamical model of the robot. A multi-objective optimization goal [...] Read more.
This paper presents a novel model-based structural optimization approach for the efficient electromechanical development of hexapod robots. First, a hexapod-design-related analysis of both optimization objectives and relevant parameters is conducted based on the derived dynamical model of the robot. A multi-objective optimization goal is proposed, which minimizes energy consumption, unwanted body motion and differences between joint torques. Then, an optimization framework is established, which utilizes a sophisticated strategy to handle the optimization problems characterized by a large set of parameters. As a result, a satisfactory result is efficiently obtained with fewer iterations. The research determines the optimal parameter set for hexapod robots, contributing to significant increases in a robot’s walking range, suppressed robot body vibrations, and both balanced and appropriate motor loads. The modular design of the proposed simulation model also offers flexibility, allowing for the optimization of other electromechanical properties of hexapod robots. The presented research focuses on the mechatronic design of the Szabad(ka)-III hexapod robot and is based on the previously validated Szabad(ka)-II hexapod robot model. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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22 pages, 2683 KiB  
Article
Improved Cubature Kalman Filtering on Matrix Lie Groups Based on Intrinsic Numerical Integration Error Calibration with Application to Attitude Estimation
by Huijuan Guo, Yan Zhou, Huiying Liu and Xiaoxiang Hu
Machines 2022, 10(4), 265; https://doi.org/10.3390/machines10040265 - 7 Apr 2022
Cited by 2 | Viewed by 2161
Abstract
This paper investigates the numerical integration error calibration problem in Lie group sigma point filters to obtain more accurate estimation results. On the basis of the theoretical framework of the Bayes–Sard quadrature transformation, we first established a Bayesian estimator on matrix Lie groups [...] Read more.
This paper investigates the numerical integration error calibration problem in Lie group sigma point filters to obtain more accurate estimation results. On the basis of the theoretical framework of the Bayes–Sard quadrature transformation, we first established a Bayesian estimator on matrix Lie groups for system measurements in Euclidean spaces or Lie groups. The estimator was then employed to develop a generalized Bayes–Sard cubature Kalman filter on matrix Lie groups that considers additional uncertainties brought by integration errors and contains two variants. We also built on the maximum likelihood principle, and an adaptive version of the proposed filter was derived for better algorithm flexibility and more precise filtering results. The proposed filters were applied to the quaternion attitude estimation problem. Monte Carlo numerical simulations supported that the proposed filters achieved better estimation quality than that of other Lie group filters in the mentioned studies. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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17 pages, 28261 KiB  
Article
Design of an Embedded Energy Management System for Li–Po Batteries Based on a DCC-EKF Approach for Use in Mobile Robots
by Arezki Abderrahim Chellal, José Gonçalves, José Lima, Vítor Pinto and Hicham Megnafi
Machines 2021, 9(12), 313; https://doi.org/10.3390/machines9120313 - 25 Nov 2021
Cited by 5 | Viewed by 2387
Abstract
In mobile robotics, since no requirements have been defined regarding accuracy for Battery Management Systems (BMS), standard approaches such as Open Circuit Voltage (OCV) and Coulomb Counting (CC) are usually applied, mostly due to the fact that employing more complicated estimation algorithms requires [...] Read more.
In mobile robotics, since no requirements have been defined regarding accuracy for Battery Management Systems (BMS), standard approaches such as Open Circuit Voltage (OCV) and Coulomb Counting (CC) are usually applied, mostly due to the fact that employing more complicated estimation algorithms requires higher computing power; thus, the most advanced BMS algorithms reported in the literature are developed and verified by laboratory experiments using PC-based software. The objective of this paper is to describe the design of an autonomous and versatile embedded system based on an 8-bit microcontroller, where a Dual Coulomb Counting Extended Kalman Filter (DCC-EKF) algorithm for State of Charge (SOC) estimation is implemented; the developed prototype meets most of the constraints for BMSs reported in the literature, with an energy efficiency of 94% and an error of SOC accuracy that varies between 2% and 8% based on low-cost components. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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19 pages, 20281 KiB  
Article
An Improved Invariant Kalman Filter for Lie Groups Attitude Dynamics with Heavy-Tailed Process Noise
by Jiaolong Wang, Chengxi Zhang, Jin Wu and Ming Liu
Machines 2021, 9(9), 182; https://doi.org/10.3390/machines9090182 - 27 Aug 2021
Cited by 6 | Viewed by 2617
Abstract
Attitude estimation is a basic task for most spacecraft missions in aerospace engineering and many Kalman type attitude estimators have been applied to the guidance and navigation of spacecraft systems. By building the attitude dynamics on matrix Lie groups, the invariant Kalman filter [...] Read more.
Attitude estimation is a basic task for most spacecraft missions in aerospace engineering and many Kalman type attitude estimators have been applied to the guidance and navigation of spacecraft systems. By building the attitude dynamics on matrix Lie groups, the invariant Kalman filter (IKF) was developed according to the invariance properties of symmetry groups. However, the Gaussian noise assumption of Kalman theory may be violated when a spacecraft maneuvers severely and the process noise might be heavy-tailed, which is prone to degrade IKF’s performance for attitude estimation. To address the attitude estimation problem with heavy-tailed process noise, this paper proposes a hierarchical Gaussian state-space model for invariant Kalman filtering: The probability density function of state prediction is defined based on student’s t distribution, while the conjugate prior distributions of the scale matrix and degrees of freedom (dofs) parameter are respectively formulated as the inverse Wishart and Gamma distribution. For the constructed hierarchical Gaussian attitude estimation state-space model, the Lie groups rotation matrix of spacecraft attitude is inferred together with the scale matrix and dof parameter using the variational Bayesian iteration. Numerical simulation results illustrate that the proposed approach can significantly improve the filtering robustness of invariant Kalman filter for Lie groups spacecraft attitude estimation problems with heavy-tailed process uncertainty. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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22 pages, 2803 KiB  
Article
A Simple Soft Computing Structure for Modeling and Control
by Hemza Redjimi and József Kázmér Tar
Machines 2021, 9(8), 168; https://doi.org/10.3390/machines9080168 - 14 Aug 2021
Cited by 6 | Viewed by 2022
Abstract
Using the interpolation/extrapolation skills of the core function of an iterative adaptive controller, a structurally simple single essential layer neural network-based topological structure is suggested with fast and explicit single-step teaching and data-retrieving abilities. Its operation does not assume massive parallelism, therefore it [...] Read more.
Using the interpolation/extrapolation skills of the core function of an iterative adaptive controller, a structurally simple single essential layer neural network-based topological structure is suggested with fast and explicit single-step teaching and data-retrieving abilities. Its operation does not assume massive parallelism, therefore it easily can be simulated by simple sequential program codes not needing sophisticated data synchronization mechanisms. It seems to be advantageous in approximate model-based common, robust, or adaptive controllers that can compensate for the effects of minor modeling imprecisions. In this structure a neuron can be in either a firing or a passive (i.e., producing zero output) state. In firing state its activation function realizes an abstract rotation that maps the desired kinematic data into the space of the necessary control forces. The activation function allows the use of a simple and fast incremental model modification for slowly varying dynamic models. Its operation is exemplified by numerical simulations for a van der Pol oscillator in free motion, and within a Computed Torque type control. To reveal the possibility for efficient model correction, a robust Variable Structure/Sliding Mode Controller is applied, too. The novel structure can be obtained by approximate experimental observations as e.g., the fuzzy models. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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Review

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26 pages, 84508 KiB  
Review
Perspectives of RealSense and ZED Depth Sensors for Robotic Vision Applications
by Vladimir Tadic, Attila Toth, Zoltan Vizvari, Mihaly Klincsik, Zoltan Sari, Peter Sarcevic, Jozsef Sarosi and Istvan Biro
Machines 2022, 10(3), 183; https://doi.org/10.3390/machines10030183 - 3 Mar 2022
Cited by 23 | Viewed by 13549
Abstract
This review paper presents an overview of depth cameras. Our goal is to describe the features and capabilities of the introduced depth sensors in order to determine their possibilities in robotic applications, focusing on objects that might appear in applications with high accuracy [...] Read more.
This review paper presents an overview of depth cameras. Our goal is to describe the features and capabilities of the introduced depth sensors in order to determine their possibilities in robotic applications, focusing on objects that might appear in applications with high accuracy requirements. A series of experiments was conducted, and various depth measuring conditions were examined in order to compare the measurement results of all the depth cameras. Based on the results, all the examined depth sensors were appropriate for applications where obstacle avoidance and robot spatial orientation were required in coexistence with image vision algorithms. In robotic vision applications where high accuracy and precision were obligatory, the ZED depth sensors achieved better measurement results. Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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