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1 – 10 of 230Bin Li, Shoukun Wang, Jinge Si, Yongkang Xu, Liang Wang, Chencheng Deng, Junzheng Wang and Zhi Liu
Dynamically tracking the target by unmanned ground vehicles (UGVs) plays a critical role in mobile drone recovery. This study aims to solve this challenge under diverse random…
Abstract
Purpose
Dynamically tracking the target by unmanned ground vehicles (UGVs) plays a critical role in mobile drone recovery. This study aims to solve this challenge under diverse random disturbances, proposing a dynamic target tracking framework for UGVs based on target state estimation, trajectory prediction, and UGV control.
Design/methodology/approach
To mitigate the adverse effects of noise contamination in target detection, the authors use the extended Kalman filter (EKF) to improve the accuracy of locating unmanned aerial vehicles (UAVs). Furthermore, a robust motion prediction algorithm based on polynomial fitting is developed to reduce the impact of trajectory jitter caused by crosswinds, enhancing the stability of drone trajectory prediction. Regarding UGV control, a dynamic vehicle model featuring independent front and rear wheel steering is derived. Additionally, a linear time-varying model predictive control algorithm is proposed to minimize tracking errors for the UGV.
Findings
To validate the feasibility of the framework, the algorithms were deployed on the designed UGV. Experimental results demonstrate the effectiveness of the proposed dynamic tracking algorithm of UGV under random disturbances.
Originality/value
This paper proposes a tracking framework of UGV based on target state estimation, trajectory prediction and UGV predictive control, enabling the system to achieve dynamic tracking to the UAV under multiple disturbance conditions.
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Keywords
Shanshuai Niu, Junzheng Wang and Jiangbo Zhao
There are various uncertain and nonlinear problems in hydraulic legged robot systems, including parameter uncertainty, unmodeled dynamics and external disturbances. This study…
Abstract
Purpose
There are various uncertain and nonlinear problems in hydraulic legged robot systems, including parameter uncertainty, unmodeled dynamics and external disturbances. This study aims to eliminate uncertainties and improve the foot trajectory tracking control performance of hydraulic legged robots, a high-performance foot trajectory tracking control method based on fixed-time disturbance observers for hydraulic legged robots is proposed.
Design/methodology/approach
First, the robot leg mechanical system model and hydraulic system model of the hydraulic legged robot are established. Subsequently, two fixed-time disturbance observers are designed to address the unmatched lumped uncertainty and match lumped uncertainty in the system. Finally, the lumped uncertainties are compensated in the controller design, and the designed motion controller also achieves fixed-time stability.
Findings
Through simulation and experiments, it can be found that the proposed tracking control method based on fixed-time observers has better tracking control performance. The effectiveness and superiority of the proposed method have been verified.
Originality/value
Both the disturbance observers and the controller achieve fixed-time stability, effectively improving the performance of foot trajectory tracking control for hydraulic legged robots.
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Keywords
Yanchao Sun, Jiayu Li, Hongde Qin and Yutong Du
Autonomous underwater vehicle (AUV) is widely used in resource prospection and underwater detection due to its excellent performance. This study considers input saturation…
Abstract
Purpose
Autonomous underwater vehicle (AUV) is widely used in resource prospection and underwater detection due to its excellent performance. This study considers input saturation, nonlinear model uncertainties and external ocean current disturbances. The containment errors can be limited to a small neighborhood of zero in finite time by employing control strategy. The control strategy can keep errors within a certain range between the trajectory followed by AUVs and their intended targets. This can mitigate the issues of collisions and disruptions in communication which may arise from AUVs being in close proximity or excessively distant from each other.
Design/methodology/approach
The tracking errors are constrained. Based on the directed communication topology, a cooperative formation control algorithm for multi-AUV systems with constrained errors is designed. By using the saturation function, state observers are designed to estimate the AUV’s velocity in six degrees of freedom. A new virtual control algorithm is designed through combining backstepping technique and the tan-type barrier Lyapunov function. Neural networks are used to estimate and compensate for the nonlinear model uncertainties and external ocean current disturbances. A neural network adaptive law is designed.
Findings
The containment errors can be limited to a small neighborhood of zero in finite time so that follower AUVs can arrive at the convex hull consisting of leader AUVs within finite time. The validity of the results is indicated by simulations.
Originality/value
The state observers are designed to approximate the speed of the AUV and improve the accuracy of the control method. The anti-saturation function and neural network adaptive law are designed to deal with input saturation and general disturbances, respectively. It can ensure the safety and reliability of the multiple AUV systems.
Details
Keywords
Zhixu Zhu, Hualiang Zhang, Guanghui Liu and Dongyang Zhang
This paper aims to propose a hybrid force/position controller based on the adaptive variable impedance.
Abstract
Purpose
This paper aims to propose a hybrid force/position controller based on the adaptive variable impedance.
Design/methodology/approach
First, the working space is divided into a force control subspace and a position subspace, the force control subspace adopts the position impedance control strategy. At the same time, the contact force model between the robot and the surface is analyzed in this space. Second, based on the traditional position impedance, the model reference adaptive control is introduced to provide an accurate reference position for the impedance controller. Then, the BP neural network is used to adjust the impedance parameters online.
Findings
The experimental results show that compared with the traditional PI control method, the proposed method has a higher flexibility, the dynamic response accommodation time is reduced by 7.688 s and the steady-state error is reduced by 30.531%. The overshoot of the contact force between the end of robot and the workpiece is reduced by 34.325% comparing with the fixed impedance control method.
Practical implications
The proposed control method compares with a hybrid force/position based on PI control method and a position fixed impedance control method by simulation and experiment.
Originality/value
The adaptive variable impedance control method improves accuracy of force tracking and solves the problem of the large surfaces with robot grinding often over-polished at the protrusion and under-polished at the concave.
Details
Keywords
Peng Gao, Xiuqin Su, Zhibin Pan, Maosen Xiao and Wenbo Zhang
This study aims to promote the anti-disturbance and tracking accuracy performance of the servo systems, in which a modified active disturbance rejection control (MADRC) scheme is…
Abstract
Purpose
This study aims to promote the anti-disturbance and tracking accuracy performance of the servo systems, in which a modified active disturbance rejection control (MADRC) scheme is proposed.
Design/methodology/approach
An adaptive radial basis function (ARBF) neural network is utilized to estimate and compensate dominant friction torque disturbance, and a parallel high-gain extended state observer (PHESO) is employed to further compensate residual and other uncertain disturbances. This parallel compensation structure reduces the burden of single ESO and improves the response speed of permanent magnet synchronous motor (PMSM) to hybrid disturbances. Moreover, the sliding mode control (SMC) rate is introduced to design an adaptive update law of ARBF.
Findings
Simulation and experimental results show that as compared to conventional ADRC and SMC algorithms, the position tracking error is only 2.3% and the average estimation error of the total disturbances is only 1.4% in the proposed MADRC algorithm.
Originality/value
The disturbance parallel estimation structure proposed in MADRC algorithm is proved to significantly improve the performance of anti-disturbance and tracking accuracy.
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Keywords
This paper aims to propose a lightweight, high-accuracy object detection model designed to enhance seam tracking quality under strong arcs and splashes condition. Simultaneously…
Abstract
Purpose
This paper aims to propose a lightweight, high-accuracy object detection model designed to enhance seam tracking quality under strong arcs and splashes condition. Simultaneously, the model aims to reduce computational costs.
Design/methodology/approach
The lightweight model is constructed based on Single Shot Multibox Detector (SSD). First, a neural architecture search method based on meta-learning and genetic algorithm is introduced to optimize pruning strategy, reducing human intervention and improving efficiency. Additionally, the Alternating Direction Method of Multipliers (ADMM) is used to perform structural pruning on SSD, effectively compressing the model with minimal loss of accuracy.
Findings
Compared to state-of-the-art models, this method better balances feature extraction accuracy and inference speed. Furthermore, seam tracking experiments on this welding robot experimental platform demonstrate that the proposed method exhibits excellent accuracy and robustness in practical applications.
Originality/value
This paper presents an innovative approach that combines ADMM structural pruning and meta-learning-based neural architecture search to significantly enhance the efficiency and performance of the SSD network. This method reduces computational cost while ensuring high detection accuracy, providing a reliable solution for welding robot laser vision systems in practical applications.
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Qixin Zhu, Wenxin Sun, Yehu Shen, Guizhong Fu, Yong Yang and Jinbin Li
This study aims to improve the control accuracy and antidisturbance performance of the manipulator with the flexible link, a combined controller, which combines the novel…
Abstract
Purpose
This study aims to improve the control accuracy and antidisturbance performance of the manipulator with the flexible link, a combined controller, which combines the novel backstepping sliding mode controller based on the extended state observer (ESO) and super-twisting sliding mode controller.
Design/methodology/approach
First, the dynamic of the system is constructed by Lagrange method and assumed mode method, and then the dynamic is decoupled by the singular perturbation theory to obtain the slow-varying subsystem and fast-varying subsystem. For the slow-varying subsystem, the novel backstepping sliding mode controller based on ESO is used to achieve joint tracking. For the fast-varying subsystem, the super-twisting sliding mode controller is used for vibration suppression. At the same time, to suppress chattering, the tanh function is used to replace the sign function in the reaching law.
Findings
The simulation results show that the combined control has better trajectory tracking performance, antiinterference performance and vibration suppression performance than traditional sliding mode control (SMC).
Originality/value
A novel backstepping sliding mode controller based on ESO is designed to guarantee the performance of the tracking trajectory. The new controller improves the converge rate. A super-twisting sliding mode controller, which can stabilize the fast-varying subsystem, is used to suppress the vibration of flexible link.
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Gan Zhan, Zhihua Chen, Zhenyu Zhang, Jigang Zhan, Wentao Yu and Jiehao Li
This study aims to address the issue of random movement and non coordination between docking mechanisms and locking mechanisms, and proposes a comprehensive dynamic docking…
Abstract
Purpose
This study aims to address the issue of random movement and non coordination between docking mechanisms and locking mechanisms, and proposes a comprehensive dynamic docking control architecture that integrates perception, planning, and motion control.
Design/methodology/approach
Firstly, the proposed dynamic docking control architecture uses laser sensors and a charge-coupled device camera to perceive the pose of the target. The sensor data are mapped to a high-dimensional potential field space and fused to reduce interference caused by detection noise. Next, a new potential function based on multi-dimensional space is developed for docking path planning, which enables the docking mechanism based on Stewart platform to rapidly converge to the target axis of the locking mechanism, which improves the adaptability and terminal docking accuracy of the docking state. Finally, to achieve precise tracking and flexible docking in the final stage, the system combines a self-impedance controller and an impedance control algorithm based on the planned trajectory.
Findings
Extensive simulations and experiments have been conducted to validate the effectiveness of the dynamic docking system and its control architecture. The results indicate that even if the target moves randomly, the system can successfully achieve accurate, stable and flexible dynamic docking.
Originality/value
This research can provide technical guidance and reference for docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.
Details
Keywords
Jun Tian, Xungao Zhong, Xiafu Peng, Huosheng Hu and Qiang Liu
Visual feedback control is a promising solution for robots work in unstructured environments, and this is accomplished by estimation of the time derivative relationship between…
Abstract
Purpose
Visual feedback control is a promising solution for robots work in unstructured environments, and this is accomplished by estimation of the time derivative relationship between the image features and the robot moving. While some of the drawbacks associated with most visual servoing (VS) approaches include the vision–motor mapping computation and the robots’ dynamic performance, the problem of designing optimal and more effective VS systems still remains challenging. Thus, the purpose of this paper is to propose and evaluate the VS method for robots in an unstructured environment.
Design/methodology/approach
This paper presents a new model-free VS control of a robotic manipulator, for which an adaptive estimator aid by network learning is proposed using online estimation of the vision–motor mapping relationship in an environment without the knowledge of statistical noise. Based on the adaptive estimator, a model-free VS schema was constructed by introducing an active disturbance rejection control (ADRC). In our schema, the VS system was designed independently of the robot kinematic model.
Findings
The various simulations and experiments were conducted to verify the proposed approach by using an eye-in-hand robot manipulator without calibration and vision depth information, which can improve the autonomous maneuverability of the robot and also allow the robot to adapt its motion according to the image feature changes in real time. In the current method, the image feature trajectory was stable in the camera field range, and the robot’s end motion trajectory did not exhibit shock retreat. The results showed that the steady-state errors of image features was within 19.74 pixels, the robot positioning was stable within 1.53 mm and 0.0373 rad and the convergence rate of the control system was less than 7.21 s in real grasping tasks.
Originality/value
Compared with traditional Kalman filtering for image-based VS and position-based VS methods, this paper adopts the model-free VS method based on the adaptive mapping estimator combination with the ADRC controller, which is effective for improving the dynamic performance of robot systems. The proposed model-free VS schema is suitable for robots’ grasping manipulation in unstructured environments.
Details
Keywords
Srikant Gupta and Pooja Singh Kushwaha
The purpose of our research on blockchain technology is to unveil its immense potential, understand its applications and implications and identify opportunities to revolutionize…
Abstract
Purpose
The purpose of our research on blockchain technology is to unveil its immense potential, understand its applications and implications and identify opportunities to revolutionize existing systems and processes. This research aims to inspire the creation of new innovative solutions for industries. By harnessing blockchain technology, organizations can pinpoint key areas that could significantly benefit from its use, such as streamlining operations, providing secure and transparent digital solutions and fortifying data security.
Design/methodology/approach
This study presents a robust multi-criteria decision-making framework for assessing blockchain drivers in selected Indian industries. We initiated with an extensive literature review to identify potential drivers. We then sought the opinions of experts in the field to validate and refine our list. This meticulous process led us to identify 26 drivers, which we categorized into five main categories. Finally, we employed the Best-Worst Method to determine the relative importance of each criterion, ensuring a comprehensive and reliable assessment.
Findings
The authors have ranked the blockchain drivers based on their degree of importance using the Best-Worst Method. This study reveals the priority of BC implementation, with the retail industry identified as the most in need, followed by the Banking and Healthcare industries. Various critical factors are identified where blockchain technology could help reduce costs, increase efficiency and enable new innovative business models.
Research limitations/implications
While this study acknowledges potential bias in driver assessment relying on literature and expert opinions, its findings carry significant practical implications. We have identified key areas where blockchain technology could be transformative by focusing on select industries. Future research should encompass other industries and real-world case studies for practical insights that could delve into the adoption challenges and benefits of blockchain technology in many other industries, thereby amplifying the relevance of our findings.
Originality/value
Blockchain is a groundbreaking, innovative technology with immense potential to revolutionize industries. Past research has explored the benefits and challenges of blockchain implementation in specific industries or sectors. This creates a gap in research regarding systematically classifying and ranking the importance of blockchain across different Indian industries. Our research seeks to address this gap by using advanced multi-criteria decision-making techniques. We aim to provide a comprehensive understanding of the significance of blockchain technology in critical Indian industries, offering valuable insights that can inform strategic decision-making and drive innovation in the country’s business landscape.
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