CERES :: Browsing by Author "Asif, Seemal"

Browsing by Author "Asif, Seemal"

Now showing 1 - 20 of 21

Open Access
Advancements in 3D x-ray imaging: development and application of a twin robot system
(Brunel University, 2024-08-31) Asif, Seemal; Hryshchenko Sumina, Yuliya; Holden, Martin; Contino, Matteo; Adiuku, Ndidiamaka; Hughes, Bryn; Plastropoulos, Angelos; Avdelidis, Nico; Webb, Phil
development of a novel twin robot system for 3D X-ray imaging integrates advanced robotic control with mobile X-ray technology to significantly enhance diagnostic accuracy and efficiency in both medical and industrial applications. Key technical aspects, including innovative design specifications and system architecture, are discussed in detail. The twin robots operate in tandem, providing comprehensive imaging capabilities with high precision. This novel approach offers potential applications ranging from medical diagnostics to industrial inspections, significantly improving over traditional imaging methods. Preliminary results demonstrate the system's effectiveness in producing detailed 3D images, underscoring its potential for wide-ranging uses. Future research will focus on optimizing image quality and automating the imaging process to increase utility and efficiency. This development signifies a step forward in integrating robotics and imaging technology, promising enhanced outcomes in various fields.
Open Access
Communication components for Human Intention Prediction – a survey
(AHFE International, 2023-07-24) Khan, Fahad; Asif, Seemal; Webb, Phil
In this review we address the communication components for human intention prediction for Human-robot collaboration (HRC). The HRC is the approach in which human and robot(s) work towards achieving the same goal. The interaction can be both levels physical and cognitive. The traditional settings of the HRC system provides fixed robot program based on waypoints or gestures. It is difficult to predefine the instructions of the situation in complex and variable environment. The understanding of human intention on dynamic basis is crucial for the success of such systems. The core character of co-existence of human and the robot is to understand the dynamic scenes of human intentions. To understand the human intention there is need to understand the components of intention communication. This paper provides comprehensive overview about the understanding the intention as communication components and modelling those components by using machine learning technology in HRC. Multiple ways of communicating intention are possible by using speech, action, gesture, haptic, physiological signals, etc. The article details various approaches to understand the human intention communication aspect particularly in the Human Robot Collaboration setting.
Open Access
Contactless medium scale industrial robot collaboration
(OMICS International, 2016-03-11) Asif, Seemal; Webb, Philip
The growing cost of High-Value/Mix and Low Volume (HMLV) industries like Aerospace is heavily based on industrial robots and manual operations done by operators [1]. Robots are excellent in repeatability by HMLV industries need changes with every single product. On the other hand human workforce is good at variability and intelligence but cost a lot as production rate is not comparable to robots and machines. There are flexible systems which have been specifically introduced for this type of industry FLEXA is one of them. But still there is need of collaboration between human and robot to get the flexible and cost effective solution [2]. A comprehensive survey has been conducted specifically on the issue of Human Robot collaboration [3] which laid out many advantages of this approach includes flexibility, cost-effectiveness and use of robot as intelligent assistant. There are several attempts have been made for Human Robot Collaboration for HMLV industry and Chen et al. attempt is one of them.
Open Access
Cost effective welding system by using AR3 robot
(IEEE, 2022-06-08) Asif, Seemal
Innovations in the field of robotics and image processing have enabled robotic welding to slowly become the new standard for companies that are heavily invested in the process. However, the cost of such autonomous systems makes them accessible to only the elite; hence, without a sizeable investment, smaller companies are left behind the competition. The article describes a cost-effective solution to the process of autonomous welding through the use of a structured light set up along with an open-source robot and its design issues. A prototype of the proposed system has been developed with the results available.
Open Access
Enhanced cell controller for aerospace manufacturing
(OMICS International, 2016-04-30) Asif, Seemal; Webb, Philip
Aerospace manufacturing industry is unique in that production typically focuses on high variety and quality but extremely low volume. Manufacturing processes are also sometimes unique and not repeatable and, hence, costly. Production is getting more expensive with the introduction of industrial robots and their cells. This paper describes the development of the Flexa Cell Coordinator (FCC), a system that is providing a solution to manage resources at assembly cell level. It can control, organise and coordinate between the resources and is capable of controlling remote cells and resources because of its distributed nature. It also gives insight of a system to the higher management via its rich reporting facility and connectivity with company systems e.g., Enterprise Resource Planner (ERP). It is able to control various kinds of cells and resources (network based) which are not limited to robots and machines. It is extendable and capable of adding multiple numbers of cells inside the system. It also provides the facility of scheduling the task to avoid the deadlocking in the process. In FCC resources (e.g., tracker) can also be shared between cells.
Open Access
Examining the societal impact and legislative requirements of deepfake technology: a comprehensive study
(EJournal Publishing, 2024-03-29) Alanazi, Sami; Asif, Seemal; Moulitsas, Irene
Deepfakes, highly realistic fabricated videos, images, or audios created using artificial intelligence algorithms, have gained widespread attention and raised concerns about their social impact and ethical implications. While initially seen as a source of entertainment and utilized in commercial applications, deepfake technology has increasingly been misused for creating adult content, blackmailing individuals, spreading misinformation, and manipulating memories. The negative consequences of deepfakes extend beyond individuals, impacting society as a whole, particularly during sensitive times like elections, where trust can be undermined. The paper looks at the social implications and legislative considerations for deepfakes content, with the goal of cultivating a thorough understanding of their impact on society. By highlighting the importance of enacting laws and regulations, the paper emphasizes the pressing need to control their widespread dissemination. Deepfakes have broad societal implications, especially during critical events like elections, eroding trust. This survey delves into deepfake complexities, aiming to foster understanding and emphasizing the urgency of regulation. The paper also discusses the positive outcomes of deepfake technology for intellectual property protection, highlighting the FORGE system developed to trick attackers who steal company documents. However, it emphasizes the risks posed by easily accessible websites that facilitate the creation of fake identification documents, increasing the likelihood of identity theft, criminal activities, and fraudulent transactions. Implementing restrictions on the use of deepfake technology involving children is also crucial to prevent harm and manipulation targeting minors.
Open Access
Exploring deepfake technology: creation, consequences and countermeasures
(Springer , 2024-12) Alanazi, Sami; Asif, Seemal
This paper presents a comprehensive examination of deepfakes, exploring their creation, production and identification. Deepfakes are videos, images or audio that are remarkably realistic and generated using artificial intelligence algorithms. While they were initially intended for entertainment and commercial use, their harmful social consequences have become more evident over time. These technologies are now being misapplied for the creation of explicit content, coercing individuals and disseminating false information, resulting in an erosion of and potentially negative societal consequences. The paper also highlights the significance of legal regulations in controlling the utilization of deepfakes and investigates methods for their identification through machine learning. In the modern digital world, comprehending the ethical and legal implications of deepfakes necessitates a thorough understanding of the phenomenon.
Open Access
A framework for controlling multiple industrial robots using mobile applications
(SciDoc Publishers, 2021-09-08) Alvarado, Daniela; Asif, Seemal
Purpose: Over the last few decades, the development of the hardware and software has enabled the application of advanced systems. In the robotics field, the UI design is an intriguing area to be explored due to the creation of devices with a wide range of functionalities in a reduced size. Moreover, the idea of using the same UI to control several systems arouses a great interest considering that this involves less learning effort and time for the users. Therefore, this paper will present a mobile application to control two industrial robots with four modes of operation. Design/methodology/approach: The smartphone was selected to be the interface due to its wide range of capabilities and the MIT Inventor App was used to create the application, whose environment is supported by Android smartphones. For the validation, ROS was used since it is a fundamental framework utilised in industrial robotics and the Arduino Uno was used to establish the data transmission between the smartphone and the board NVIDIA Jetson TX2. In MIT Inventor App, the graphical interface was created to visualize the options available in the app whereas two scripts in python were programmed to perform the simulations in ROS and carry out the tests. Findings: The results indicated that the use of the sliders to control the robots is more favourable than the Orientation Sensor due to the sensibility of the sensor and human limitations to hold the smartphone perfectly still. Another important finding was the limitations of the autonomous mode, in which the robot grabs an object. In this case, the configuration of the Kinect camera and the controllers has a significant impact on the success of the simulation. Finally, it was observed that the delay was appropriate despite the use of the Arduino UNO to transfer the data between the Smartphone and the Nvidia Jetson TX2. Originality/value: The following points show the contributions of this paper to the robotic field. • Developed a robust application combining four different modes of functionality. • Create a program with an intuitive interface and simple use that allows controlling different robotics arms with just one UI. • Evaluate the applicability of the simulated industrial robots in ROS since the projects must be tested in a framework before implementing it in real robots.
Open Access
Human facial emotion recognition for adaptive human robot collaboration in manufacturing
(Brunel University, 2024-08-31) Khan, Fahad; Asif, Seemal; Webb, Phil
The integration of robots into various industries, including manufacturing, has introduced new challenges in achieving efficient human-robot collaboration. A crucial aspect of successful collaboration is the ability of robots to understand and respond to human emotions. In the context of human-robot collaboration in manufacturing, accurately predicting human emotions is essential for enhancing efficiency and safety. This paper presents a setup for human emotion detection, focusing on facial emotion recognition. The proposed model and descriptive summary involve the utilising state-of-the-art algorithms such as AlexNet, HaarCascade (HCC), MTCNN (Multi-Task Cascaded Convolutional Neural Networks), and SVM (Support Vector Machine), applied to datasets like CK+, JAFFE, and AffectNet. The performance of each facial recognition model is evaluated in real-time scenarios, resulting in significant progress with an accuracy improvement from 40% to 78.1%. These results demonstrate the effectiveness of the approach in enabling adaptive robot control based on human emotions and enhancing collaboration quality. This research uniquely integrates facial emotion recognition and robot control to enable adaptive responses during human-robot collaboration in manufacturing settings. By understanding and responding to human emotions, robots can improve their interactions with humans, leading to increased productivity and improved overall collaboration efficiency.
Open Access
An improved cell controller for the aerospace manufacturing
(Cranfield University Press, 2013-09-19) Asif, Seemal; Webb, Philip
The aerospace manufacturing industry is unique in that production typically focuses on high variety and quality but low volume. Existing flexible manufacturing cells are limited to certain types of machines, robots and cells which makes it difficult to introduce any changes. In this paper idea of treating machines, robots, any hardware and software as resource has been introduced. It describes the development of the Flexa Cell Coordinator (FCC), a system that is providing a solution to manage cells and their resources in a new flexible manner. It can control, organise and coordinate between cells and resources and is capable of controlling remote cells because of its distributed nature. It also provides connectivity with company systems e.g., Enterprise Resource Planner (ERP). It is extendable and capable of adding multiple cells inside the system. In FCC resources (e.g., tracker) can also be shared between cells. The paper presents its development and results of initial successful testing.
Open Access
Kinematics analysis of 6-DoF articulated robot with spherical wrist
(Hindawi Publishing Corporation, 2021-02-02) Asif, Seemal; Webb, Philip
The aim of the paper is to study the kinematics of the manipulator. The articulated robot with a spherical wrist has been used for this purpose. The Comau NM45 Manipulator has been chosen for the kinematic model study. The manipulator contains six revolution joints. Pieper’s approach has been employed to study the kinematics (inverse) of the robot manipulator. Using this approach, the inverse kinematic problem is divided into two small less complex problems. This reduces the time of analysing the manipulator kinematically. The forward and inverse kinematics has been performed, and mathematical solutions are detailed based on D-H (Denavit–Hartenberg) parameters. The kinematics solution has been verified by solving the manipulator’s motion. It has been observed that the model is accurate as the motion trajectory was smoothly followed by the manipulator.
Open Access
Managing delays for realtime error correction and compensation of an industrial robot in an open network
(MDPI, 2023-08-28) Asif, Seemal; Webb, Phil
The calibration of articulated arms presents a substantial challenge within the manufacturing domain, necessitating sophisticated calibration systems often reliant on the integration of costly metrology equipment for ensuring high precision. However, the logistical complexities and financial burden associated with deploying these devices across diverse systems hinder their widespread adoption. In response, Industry 4.0 emerges as a transformative paradigm by enabling the integration of manufacturing devices into networked environments, thereby providing access through cloud-based infrastructure. Nonetheless, this transition introduces a significant concern in the form of network-induced delays, which can significantly impact realtime calibration procedures. To address this pivotal challenge, the present study introduces an innovative framework that adeptly manages and mitigates network-induced delays. This framework leverages two key components: controller and optimiser, specifically the MPC (Model Predictive Controller) in conjunction with the Extended Kalman Filter (EKF), and a Predictor, characterised as the Dead Reckoning Model (DRM). Collectively, these methodologies are strategically integrated to address and ameliorate the temporal delays experienced during the calibration process. Significantly expanding upon antecedent investigations, the study transcends prior boundaries by implementing an advanced realtime error correction system across networked environments, with particular emphasis on the intricate management of delays originating from network traffic dynamics. The fundamental aim of this research extension is twofold: firstly, it aims to enhance realtime system performance on open networks, while concurrently achieving an impressive level of error correction precision at 0.02 mm. The employment of the proposed methodologies is anticipated to effectively surmount the intricacies and challenges associated with network-induced delays. Subsequently, this endeavour serves to catalyse accurate and efficient calibration procedures in the context of realtime manufacturing scenarios. This research significantly advances the landscape of error correction systems and lays a robust groundwork for the optimised utilisation of networked manufacturing devices within the dynamic realm of Industry 4.0 applications.
Open Access
Networked control system – an overview
(Foundation of Computer Science, 2015-04-22) Asif, Seemal; Webb, Philip
Networked Control System (NCS) is fetching researchers’ interest from many decades. It’s been used in industry which range from manufacturing, automobile, aviation, aerospace to military. This paper gives the general architecture of NCS and its fundamental routes. It also touches to its advantages and disadvantages and some of the popular controller which include PID (Proportional-Integral-Derivative) and MPC (Model Predictive Control).
Open Access
Rapid and automated configuration of robot manufacturing cells
(Elsevier, 2025-04-01) Asif, Seemal; Bueno, Mikel; Ferreira, Pedro; Anandan, Paul; Zhang, Ze; Yao, Yue; Ragunathan, Gautham; Tinkler, Lloyd; Sotoodeh-Bahraini, Masoud; Lohse, Niels; Webb, Phil; Hutabarat, Windo; Tiwari, Ashutosh
This study presents the Reconfigurable and Responsive Robot Manufacturing (R3M) architecture, a novel framework engineered to autonomously adapt to fluctuating product variants and demands within manufacturing environments. At the heart of R3M lies an integrated architecture that ensures a seamless data flow between critical modules, facilitated by an advanced communication platform. These modules are central to delivering a range of services crucial for operational efficiency. Key to the architecture is the incorporation of Automated Risk Assessment aligned with ISO-12100 standards, utilizing ROS2 Gazebo for the dynamic modification of robot skills in a plug-and-produce manner. The architecture's unique approach to requirements definition employs AutomationML (AML), enabling effective system integration and the consolidation of varied information sources. This is achieved through the innovative use of skill-based concepts and AML Class Libraries, enhancing the system's adaptability and integration within manufacturing settings. The narrative delves into the intricate descriptions of products, equipment, and processes within the AML framework, highlighting the strategic consideration of profitability in the product domain and distinguishing between atomic and composite skills in equipment characterization. The process domain serves as an invaluable knowledge repository, bridging the gap between high-level product demands and specific equipment capabilities via process patterns. The culmination of these elements within the R3M framework provides a versatile and scalable solution poised to revolutionize manufacturing processes. Empirical results underscore the architecture's robust perception abilities, with a particular focus on a real-world application in robotic lamination stacking, elucidating both the inherent challenges and the tangible outcomes of the R3M deployment.
Open Access
Realtime calibration of an industrial robot
(MDPI, 2022-09-30) Asif, Seemal; Webb, Phil
In large scale, complex and low volume manufacturing systems, robotics are now considered unavoidable for automating the factory operations. The aerospace industry focuses on a high variety and quality but extremely low volume. The precision it requires for numerous tasks is unique and distinct from any other manufacturing industry. This can comprise accurate position, module assembly, inspection, fastening, etc. The scale of the robot invites different types of errors during operation, which can be either because of the kinematics of the robot or because of the environment (noise, temperature, load, etc.). There are packages available from robot manufacturers for the correction and compensation of errors on the robot to achieve accuracy. There are two associated problems: 1. cost and 2. static nature. They are very costly and they do not provide correction in realtime fashion (dynamic); the robot stops, waits for the correction, and then moves to the next position. The external tool to monitor the accuracy also requires attaching with the robot permanently. These are dedicated resources. These tools for accurate measurement are expensive and attached permanently to a robot, which means wastage of resources. These measuring tools are called metrology devices and attaching these devices and the robot to the network means that other robots/machines can also use these expensive tools for measurement. Our aim was to address two problems in this project: 1. calibration (error correction and compensation of robot) and 2. dynamic and realtime processing. It helped to perform the dynamic error correction and the compensation of an industrial robot. The results showed the error correction was achieved in the region of 0.02 mm.
Open Access
Software system integration - Middleware - an overview
(Foundation of Computer Science, 2015-07-01) Asif, Seemal; Webb, Philip
The integration of different softwares written in different language and based on different platforms can be tricky. In that situation a middleware is necessary to enable the communication between different softwares. The middleware enables the software system not only to share data but also share the services. This paper gives an overview of some of middleware technologies which can be used to integrate different software systems.
Open Access
A study on centralised and decentralised swarm robotics architecture for part delivery system
(Crimson Publishers, 2021-10-11) Dimakos, Angelos; Woodhall, Daniel; Asif, Seemal
Drones are also known as UAVs are originally designed for military purposes. With the technological advances, they can be seen in most of the aspects of life from filming to logistics. The increased use of drones made it sometimes essential to form a collaboration between them to perform the task efficiently in a defined process. This paper investigates the use of a combined centralised and decentralised architecture for the collaborative operation of drones in a parts delivery scenario to enable and expedite the operation of the factories of the future. The centralised and decentralised approaches were extensively researched, with experimentation being undertaken to determine the appropriateness of each approach for this use-case. Decentralised control was utilised to remove the need for excessive communication during the operation of the drones, resulting in smoother operations. Initial results suggested that the decentralised approach is more appropriate for this use-case. The individual functionalities necessary for the implementation of a decentralised architecture were proven and assessed, determining that a combination of multiple individual functionalities, namely VSLAM, dynamic collision avoidance and object tracking, would give an appropriate solution for use in an industrial setting. A final architecture for the parts delivery system was proposed for future work, using a combined centralised and decentralised approach to combat the limitations inherent in each architecture.
Open Access
Towards robot software abstraction: ROS 2-based framework for object handling within a robot cell
(IEEE, 2024-08-18) Viso, Mikel Bueno; Huang, Jingjing; Asif, Seemal; Khan, Fahad; Webb, Phil
Recent advancements in industrial automation have led to the development of increasingly adaptable and reconfigurable systems, driven by the necessity for flexibility and efficiency in manufacturing. This paper introduces a ROS 2-based software framework tailored for object handling within a robot cell, addressing challenges pertaining to reconfigurability, modularity, and interoperability. The proposed solution simplifies the deployment process of robotic applications and provides a standardized ROS 2-based platform, making it particularly beneficial for small and medium automation enterprises that require frequent reprogramming and adaptation of robot cells to different settings. By ensuring software and hardware agnosticism, the framework presents a comprehensive pipeline for designing, developing, and deploying object pick-and-place applications, demonstrated through an automated kitting use-case where a robot sorts industrial spare parts from a conveyor belt using a simple camera. The system integrates real-time object detection and classification capabilities with ROS 2 to facilitate effective communication between perception and robot action. This research advocates for open-source solutions and collaboration, aiming to enhance the adaptability and efficiency of robotic solutions across diverse industrial applications.
Open Access
Understanding deepfakes: a comprehensive analysis of creation, generation, and detection
(AHFE International, 2023-07-24) Alanazi, Sami; Asif, Seemal
This paper provides a comprehensive analysis of deepfakes, focusing on their creation, generation, and detection. Deepfakes are realistic fabricated videos, images, or audios generated using artificial intelligence algorithms. While initially seen as a source of entertainment and commercial applications, the negative social consequences of deepfakes have become apparent. They are misused for creating adult content, blackmailing individuals, and spreading misinformation, leading to a decline in trust and potential societal implications. The paper also discusses the importance of legislation in regulating the use of deepfakes and explores techniques for their detection, including machine learning and natural language processing. Understanding deepfakes is essential to address their ethical and legal implications in today's digital landscape.
Open Access
Unlocking the potential of robot manipulators: seamless integration framework
(IEEE, 2024-08-28) Bueno, Mikel; Bernardino, Irene; Asif, Seemal; Webb, Phil
This study introduces a groundbreaking framework designed to enhance the adaptability and efficiency of robot manipulators in manufacturing, leveraging ROS 2 and a modular middleware to transcend traditional robotic constraints. The framework's efficacy is exemplified through a pick-and-place task, serving not merely as a demonstration but as robust evidence of the framework's ability to enable complex object manipulation tasks far beyond repetitive activities. By integrating advanced perception capabilities with a YOLOv8-based object detection model and an OpenCV-based pose estimation module, the framework showcases a seamless interaction between sophisticated software tools and robotic hardware. This integration not only simplifies the incorporation of intelligent components into robotic systems but also significantly broadens their applicability and enhances efficiency across diverse tasks and applications. The use-case, therefore, stands as compelling evidence of the framework's potential to revolutionize industrial and collaborative robotics, providing a unified and adaptable platform for the development, testing, and deployment of robotic solutions in modern manufacturing settings. The research aims to simplify the integration of intelligent components into robotic systems, thereby extending their utility and efficiency across a broader range of tasks and applications, ultimately advancing the capabilities of industrial and collaborative robotics for modern manufacturing needs.