Search results

1 – 10 of over 71000
To view the access options for this content please click here
Article
Publication date: 18 October 2021

Zafer Bingul and Oguzhan Karahan

The purpose of this paper is to address a fractional order fuzzy PID (FOFPID) control approach for solving the problem of enhancing high precision tracking performance and…

Abstract

Purpose

The purpose of this paper is to address a fractional order fuzzy PID (FOFPID) control approach for solving the problem of enhancing high precision tracking performance and robustness against to different reference trajectories of a 6-DOF Stewart Platform (SP) in joint space.

Design/methodology/approach

For the optimal design of the proposed control approach, tuning of the controller parameters including membership functions and input-output scaling factors along with the fractional order rate of error and fractional order integral of control signal is tuned with off-line by using particle swarm optimization (PSO) algorithm. For achieving this off-line optimization in the simulation environment, very accurate dynamic model of SP which has more complicated dynamical characteristics is required. Therefore, the coupling dynamic model of multi-rigid-body system is developed by Lagrange-Euler approach. For completeness, the mathematical model of the actuators is established and integrated with the dynamic model of SP mechanical system to state electromechanical coupling dynamic model. To study the validness of the proposed FOFPID controller, using this accurate dynamic model of the SP, other published control approaches such as the PID control, FOPID control and fuzzy PID control are also optimized with PSO in simulation environment. To compare trajectory tracking performance and effectiveness of the tuned controllers, the real time validation trajectory tracking experiments are conducted using the experimental setup of the SP by applying the optimum parameters of the controllers. The credibility of the results obtained with the controllers tuned in simulation environment is examined using statistical analysis.

Findings

The experimental results clearly demonstrate that the proposed optimal FOFPID controller can improve the control performance and reduce reference trajectory tracking errors of the SP. Also, the proposed PSO optimized FOFPID control strategy outperforms other control schemes in terms of the different difficulty levels of the given trajectories.

Originality/value

To the best of the authors’ knowledge, such a motion controller incorporating the fractional order approach to the fuzzy is first time applied in trajectory tracking control of SP.

Details

Industrial Robot: the international journal of robotics research and application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-991X

Keywords

To view the access options for this content please click here
Article
Publication date: 9 September 2021

Xiao Bo Liang, Xinghua Qu, YuanJun Zhang, Lianyin Xu and Fumin Zhang

Laser absolute distance measurement has the characteristics of high precision, wide range and non-contact. In laser ranging system, tracking and aiming measurement point…

Abstract

Purpose

Laser absolute distance measurement has the characteristics of high precision, wide range and non-contact. In laser ranging system, tracking and aiming measurement point is the precondition of automatic measurement. To solve this problem, this paper aims to propose a novel method.

Design/methodology/approach

For the central point of the hollow angle coupled mirror, this paper proposes a method based on correlation filtering and ellipse fitting. For non-cooperative target points, this paper proposes an extraction method based on correlation filtering and feature matching. Finally, a visual tracking and aiming system was constructed by combining the two-axis turntable, and experiments were carried out.

Findings

The target tracking algorithm has an accuracy of 91.15% and a speed of 19.5 frames per second. The algorithm can adapt to the change of target scale and short-term occlusion. The mean error and standard deviation of the center point extraction of the hollow Angle coupling mirror are 0.20 and 0.09 mm. The mean error and standard deviation of feature points matching for non-cooperative target were 0.06 mm and 0.16 mm. The visual tracking and aiming system can track a target running at a speed of 0.7 m/s, aiming error mean is 1.74 pixels and standard deviation is 0.67 pixel.

Originality/value

The results show that this method can achieve fast and high precision target tracking and aiming and has great application value in laser ranging.

Details

Industrial Robot: the international journal of robotics research and application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-991X

Keywords

To view the access options for this content please click here
Article
Publication date: 30 August 2021

Jinchao Huang

Multi-domain convolutional neural network (MDCNN) model has been widely used in object recognition and tracking in the field of computer vision. However, if the objects to…

Abstract

Purpose

Multi-domain convolutional neural network (MDCNN) model has been widely used in object recognition and tracking in the field of computer vision. However, if the objects to be tracked move rapid or the appearances of moving objects vary dramatically, the conventional MDCNN model will suffer from the model drift problem. To solve such problem in tracking rapid objects under limiting environment for MDCNN model, this paper proposed an auto-attentional mechanism-based MDCNN (AA-MDCNN) model for the rapid moving and changing objects tracking under limiting environment.

Design/methodology/approach

First, to distinguish the foreground object between background and other similar objects, the auto-attentional mechanism is used to selectively aggregate the weighted summation of all feature maps to make the similar features related to each other. Then, the bidirectional gated recurrent unit (Bi-GRU) architecture is used to integrate all the feature maps to selectively emphasize the importance of the correlated feature maps. Finally, the final feature map is obtained by fusion the above two feature maps for object tracking. In addition, a composite loss function is constructed to solve the similar but different attribute sequences tracking using conventional MDCNN model.

Findings

In order to validate the effectiveness and feasibility of the proposed AA-MDCNN model, this paper used ImageNet-Vid dataset to train the object tracking model, and the OTB-50 dataset is used to validate the AA-MDCNN tracking model. Experimental results have shown that the augmentation of auto-attentional mechanism will improve the accuracy rate 2.75% and success rate 2.41%, respectively. In addition, the authors also selected six complex tracking scenarios in OTB-50 dataset; over eleven attributes have been validated that the proposed AA-MDCNN model outperformed than the comparative models over nine attributes. In addition, except for the scenario of multi-objects moving with each other, the proposed AA-MDCNN model solved the majority rapid moving objects tracking scenarios and outperformed than the comparative models on such complex scenarios.

Originality/value

This paper introduced the auto-attentional mechanism into MDCNN model and adopted Bi-GRU architecture to extract key features. By using the proposed AA-MDCNN model, rapid object tracking under complex background, motion blur and occlusion objects has better effect, and such model is expected to be further applied to the rapid object tracking in the real world.

Details

International Journal of Intelligent Computing and Cybernetics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1756-378X

Keywords

To view the access options for this content please click here
Article
Publication date: 7 June 2021

Sixian Chan, Jian Tao, Xiaolong Zhou, Binghui Wu, Hongqiang Wang and Shengyong Chen

Visual tracking technology enables industrial robots interacting with human beings intelligently. However, due to the complexity of the tracking problem, the accuracy of…

Abstract

Purpose

Visual tracking technology enables industrial robots interacting with human beings intelligently. However, due to the complexity of the tracking problem, the accuracy of visual target tracking still has great space for improvement. This paper aims to propose an accurate visual target tracking method based on standard hedging and feature fusion.

Design/methodology/approach

For this study, the authors first learn the discriminative information between targets and similar objects in the histogram of oriented gradients by feature optimization method, and then use standard hedging algorithms to dynamically balance the weights between different feature optimization components. Moreover, they penalize the filter coefficients by incorporating spatial regularization coefficient and extend the Kernelized Correlation Filter for robust tracking. Finally, a model update mechanism to improve the effectiveness of the tracking is proposed.

Findings

Extensive experimental results demonstrate the superior performance of the proposed method comparing to the state-of-the-art tracking methods.

Originality/value

Improvements to existing visual target tracking algorithms are achieved through feature fusion and standard hedging algorithms to further improve the tracking accuracy of robots on targets in reality.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

To view the access options for this content please click here
Article
Publication date: 10 June 2021

Bingjie Xu, Shuai Ji, Chengrui Zhang, Chao Chen, Hepeng Ni and Xiaojian Wu

Trajectory tracking error of robotic manipulator has limited its applications in trajectory tracking control systems. This paper aims to improve the trajectory tracking

Abstract

Purpose

Trajectory tracking error of robotic manipulator has limited its applications in trajectory tracking control systems. This paper aims to improve the trajectory tracking accuracy of robotic manipulator, so a linear-extended-state-observer (LESO)-based prescribed performance controller is proposed.

Design/methodology/approach

A prescribed performance function with the convergence rate, maximum overshoot and steady-state error is derived for the output error transformation, whose stability can guarantee trajectory tracking accuracy of the original robotic system. A LESO is designed to estimate and eliminate the total disturbance, which neither requires a detailed system model nor a heavy computation load. The stability of the system is proved via the Lyapunov theory.

Findings

Comparative experimental results show that the proposed controller can achieve better trajectory tracking accuracy than proportional-integral-differential control and linear active disturbance rejection control.

Originality/value

In the LESO-based prescribed performance control (PPC), the LESO was incorporated into the PPC design, it solved the problem of stabilizing the complex transformed system and avoided the costly offline identification of dynamic model and estimated and eliminated the total disturbance in real-time with light computational burden. LESO-based PPC further improved control accuracy on the basis of linear-active-disturbance-rejection-control. The new proposed method can reduce the trajectory tracking error of the robotic manipulators effectively on the basis of simplicity and stability.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 4
Type: Research Article
ISSN: 0143-991X

Keywords

To view the access options for this content please click here
Article
Publication date: 8 June 2021

Bill Marino

The integration of third-party resources on library websites may be inadvertently contributing to surveillance technologies without user knowledge. This study set out to…

Abstract

Purpose

The integration of third-party resources on library websites may be inadvertently contributing to surveillance technologies without user knowledge. This study set out to determine the prevalence of third-party tracking cookies on Association of Research Libraries (ARL) member homepages, the entities that are tracking users and for what purpose and what control users have over their cookie preferences.

Design/methodology/approach

Homepages from the 124 ARL member libraries were visited. Evidence of a privacy or cookie statement was collected and cookie logs were captured. This data were compared against the Disconnect list of known trackers and analyzed to determine the extent to which third-party tracking cookies were used across ARL sites, who was setting the cookies and for what purpose, and whether this use differed with regards to a library's identifying features.

Findings

It was determined that many ARL libraries do contribute to the ability to track a user's activity across the web, with one-third containing third-party tracking cookies. A user's contact with tracking cookies is influenced by various traits defining the institution. Users are given very little control over the cookies logged on their machines.

Originality/value

This study explores library efforts to protect user privacy, adopting an introspective approach that focuses on library websites. It will provide discussion points for librarians to question not only what third-party tracking cookies are present on their sites and why, but also how to educate their users about privacy issues.

Details

Reference Services Review, vol. 49 no. 2
Type: Research Article
ISSN: 0090-7324

Keywords

To view the access options for this content please click here

Abstract

Details

Travel Survey Methods
Type: Book
ISBN: 978-0-08-044662-2

To view the access options for this content please click here

Abstract

Details

Review of Marketing Research
Type: Book
ISBN: 978-0-85724-726-1

To view the access options for this content please click here
Book part
Publication date: 24 September 2018

Deborah Lupton and Gavin J. D. Smith

In this chapter, we draw on our study involving interviews with Australians who identify as current self-trackers to discuss why and how they monitor themselves. Our…

Abstract

In this chapter, we draw on our study involving interviews with Australians who identify as current self-trackers to discuss why and how they monitor themselves. Our approach for analysing self-tracking practices is based on a sociomaterial perspective, viewing enactments of voluntary self-tracking as shifting heterogeneous assemblages, bringing together diverse actors who are both human and non-human. We use vignettes to illustrate the ways in which our participants enacted self-tracking and to identify some of the diverse meanings and motivations that mediate decisions to self-track and resultant uses of the information thus generated. We found that a varied range of self-tracking practices were taken up by our interviewees, including not only digital devices and methods, but also recording their details using pen-and-paper, or simply maintaining mental awareness and using memory. We identified several agential capacities in our participants’ accounts of why and how they monitor themselves. These capacities are interrelated, but can be loosely grouped under the headings of ‘self-improvement’, ‘exerting control’ and ‘identifying patterns and achieving goals’. They are motivators and facilitators of monitoring practices. The broader sociocultural contexts in which monitoring of the body/self is undertaken were also revealed in the participants’ accounts. These include ideas about the moral virtues of self-responsibility and the individual management of life circumstances to avoid chaos and risk, and the notion that monitoring practices can successfully achieve these virtues.

To view the access options for this content please click here
Book part
Publication date: 24 September 2018

Thomas Blomseth Christiansen, Dorthe Brogård Kristensen and Jakob Eg Larsen

This chapter provides an insider perspective on the Quantified Self (QS) community. It is argued that the overall approach and methods used in the QS community have not…

Abstract

This chapter provides an insider perspective on the Quantified Self (QS) community. It is argued that the overall approach and methods used in the QS community have not been adequately described. Consequently, the aim of the chapter is to give an account of the work performed by self-trackers in what we coin the 1-Person-Laboratory (1PL). Additionally, the chapter describes other aspects of the 1PL, for example the methods, procedures and instrumentation that are being used and the knowledge sharing taking place in the QS community. With a point of departure in empirical cases it is demonstrated how QS self-trackers put their own questions, observations and subjective experience front and centre by using their own instrumentation and data sets in their personal laboratories. In the 1PL, the causalities that are looked for are not aimed at generalisation to an entire population; on the contrary, the causal connections on the level of the person are essential for discovery by the individual.

1 – 10 of over 71000