terrin babu pulikottil - Academia.edu (original) (raw)

Papers by terrin babu pulikottil

One of the major issues for the success of assistive robotics concerns the question whether patie... more One of the major issues for the success of assistive robotics concerns the question whether patients not only accept the technology and profit from it, but also whether they can effectively use it. This is especially relevant when patients are highly impaired and present several functional limitations. Therefore, it is important to enable patients to control robots with alternative methods during their activities of daily living. This work deals with the development of a voice control system based on the ROS middleware framework. The voice control was customized on the JACO2(Kinova Technology, Montreal, QC, Canada), a 6 degree-of-freedom assistive robotic manipulator. Two subjects with different impairments due to a neurodegenerative disease tested the robot for usability controlling it through the JACO2joystick and the developed voice control system. Both subjects used the voice control system successfully and scored highly its usability. The most impaired subject preferred the voice control while, by contrast, the less impaired one preferred to use the joystick. Preliminary results showed good usability of the system, which could be an important aid for highly impaired people.

Springer eBooks, Jun 30, 2021

Chapter "Predictive Manufacturing: Enabling Technologies, Frameworks and Applications" was previo... more Chapter "Predictive Manufacturing: Enabling Technologies, Frameworks and Applications" was previously published non-open access. It has now been changed to open access under a CC BY 4.0 license and the copyright holder updated to 'The Author(s)'. The book has also been updated with this change.

IEEE Access, 2023

The concept of smart manufacturing has attracted huge attention in the last years as an answer to... more The concept of smart manufacturing has attracted huge attention in the last years as an answer to the increasing complexity, heterogeneity, and dynamism of manufacturing ecosystems. This vision embraces the notion of autonomous and self-organized elements, capable of self-management and self-decision-making under a context-aware and intelligent infrastructure. While dealing with dynamic and uncertain environments, these solutions are also contributing to generating social impact and introducing sustainability into the industrial equation thanks to the development of task-specific resources that can be easily adapted, re-used, and shared. A lot of research under the context of self-organization in smart manufacturing has been produced in the last decade considering different methodologies and developed under different contexts. Most of these works are still in the conceptual or experimental stage and have been developed under different application scenarios. Thus, it is necessary to evaluate their design principles and potentiate their results. The objective of this paper is threefold. First, to introduce the main ideas behind self-organization in smart manufacturing. Then, through a systematic literature review, describe the current status in terms of technological and implementation details, mechanisms used, and some of the potential future research directions. Finally, the presentation of an outlook that summarizes the main results of this work and their interrelation to facilitate the development of self-organized manufacturing solutions. By providing a holistic overview of the field, we expect that this work can be used by academics and practitioners as a guide to generate awareness of possible requirements, industrial challenges, and opportunities that future self-organizing solutions can have towards a smart manufacturing transition. INDEX TERMS Cyber-physical production systems, smart manufacturing, self-organization, complexity theory, artificial intelligence, biologicalisation. LUIS A. ESTRADA-JIMENEZ received the B.Sc. degree in electronic and control engineering from Escuela Politecnica Nacional, Ecuador, in 2016, and the M.Sc. degree in mechatronics engineering from the University of Oviedo, Spain, in 2019. He is currently pursuing the Ph.D. degree in electrical and computer engineering with the Nova University of Lisbon, Portugal. His master's thesis was developed at the Department of Modular Automation, FESTO, Germany. He is also working with the UNINOVA Research Institute, and also working as an Early Stage Researcher with the Digital Manufacturing and Design Training Network (DIMAND), funded by the European Union. His research interests include self-organization and automation in smart manufacturing systems and the application of artificial intelligence in industrial environments.

IEEE Access

Big data is defined as a large set of data that could be structured or unstructured. In manufactu... more Big data is defined as a large set of data that could be structured or unstructured. In manufacturing shop-floor, big data incorporates data collected at every stage of the production process. This includes data from machines, connecting devices, and even manufacturing operators. The large size of the data available on the manufacturing shop-floor presents a need for the establishment of tools and techniques along with associated best practices to leverage the advantage of data-driven performance improvement and optimization. There also exists a need for a better understanding of the approaches and techniques at various stages of the data life cycle. In the work carried out, the data life-cycle in shop-floor is studied with a focus on each of the components-Data sources, collection, transmission, storage, processing, and visualization. A narrative literature review driven by two research questions is provided to study trends and challenges in the field. The selection of papers is supported by an analysis of n-grams. Those are used to comprehensively characterize the main technological and methodological aspects and as starting point to discuss potential future research directions. A detailed review of the current trends in different data life cycle stages is provided. In the end, the discussion of the existing challenges is also presented. INDEX TERMS Big data, data life cycle, intelligent manufacturing, machine learning, literature review.

2022 IEEE International Conference on Industrial Technology (ICIT), Aug 22, 2022

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ), 2021

The advent of Industry 4.0 and the development of future industrial applications can be achieved ... more The advent of Industry 4.0 and the development of future industrial applications can be achieved using Cyber-Physical Systems (CPS). This technological development invokes high levels of communication and computation in the form of an interconnected network of industrial resources. Multi-agent systems precisely can empower such technological evolution by introducing properties like decentralisation, autonomy, flexibility, social ability and modularity to the industrial context. In this regard, the current work surveys recent multi-agent based manufacturing approaches and provides a general vision of current trends focusing on frameworks/architectures, complementary technologies and common applications. This article, ends with an integrated discussion of emerging agent-based industrial challenges, a general conclusion and final remarks.

2021 62nd International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS), 2021

Smart industry appears as the result of a continuous evolution of sociological factors, economica... more Smart industry appears as the result of a continuous evolution of sociological factors, economical changes and several technological enablers i.e., Artificial Intelligence, Cloud Computing, Internet of things, etc. Its main objective responds to the need to streamline and make more flexible industrial processes by having high levels of process automation and by supporting operators with thinking activities. While a lot of research is being carried out to push such technical endeavour, we notice a considerable gap in human centred features more specifically empathetic and emotive skills and the consideration of such soft skills in incoming new generation of industry. Such soft skills are revised by trans-disciplinary fields i.e., Feeling economy and can be applied and harmonised with the current Smart industry conception. Thus, main objective of this work is to introduce and discuss a new model and initial ideas of a new generation of industry with a deeper focus on affective, emotive and deeply human-centring namely “Feeling Smart Industry”.

Advances in Systems Analysis, Software Engineering, and High Performance Computing, 2021

Interoperability in smart manufacturing refers to how interconnected cyber-physical components ex... more Interoperability in smart manufacturing refers to how interconnected cyber-physical components exchange information and interact. This is still an exploratory topic, and despite the increasing number of applications, many challenges remain open. This chapter presents an integrative framework to understand common practices, concepts, and technologies used in trending research to achieve interoperability in production systems. The chapter starts with the question of what interoperability is and provides an alternative answer based on influential works in the field, followed by the presentation of important reference models and their relation to smart manufacturing. It continues by discussing different types of interoperability, data formats, and common ontologies necessary for the integration of heterogeneous systems and the contribution of emerging technologies in achieving interoperability. This chapter ends with a discussion of a recent use case and final remarks.

The use of multi-agent systems (MAS) as a distributed control method for shop-floor manufacturing... more The use of multi-agent systems (MAS) as a distributed control method for shop-floor manufacturing control applications has been extensively researched. MAS provides new implementation solutions for smart manufacturing requirements such as the high dynamism and flexibility required in modern manufacturing applications. MAS in smart manufacturing is becoming increasingly important to achieve increased automation of machines and other components. Emerging technologies like artificial intelligence, cloud-based infrastructures, and cloud computing can also provide systems with intelligent, autonomous, and more scalable solutions. In the current work, a decision-making framework is proposed based on the combination of MAS cloud computing, agent technology, and machine learning. The framework is demonstrated in a quality control use case with vision inspection and agent-based control. The experiment utilizes a cloud-based machine learning pipeline for part classification and agent technology for routing. The results show the applicability of the framework in real-world scenarios bridging cloud service-oriented architecture with agent technology for production systems.

Robotics and Computer-Integrated Manufacturing, 2021

A key challenge in human-robot shared workspace is defining the decision criterion to select the ... more A key challenge in human-robot shared workspace is defining the decision criterion to select the next task for a fluent, efficient and safe collaboration. While working with robots in an industrial environment, tasks may comply with precedence constraints to be executed. A typical example of precedence constraint in industry occurs at an assembly station when the human cannot perform a task before the robot ends on its own. This paper presents a methodology based on the Maximum Entropy Inverse Optimal Control for the identification of a probability distribution over the human goals, packed into a software tool for human-robot shared-workspace collaboration. The software analyzes the human goal and the goal precedence constraints, and it is able to identify the best robot goal along with the relative motion plan. The approach used is, an algorithm for the management of goal precedence constraints and the Partially Observable Markov Decision Process (POMDP) for the selection of the next robot action. A comparison study with 15 participants was carried out in a real world assembly station. The experiment focused on evaluating the task fluency, the task efficiency and the human satisfaction. The presented model displayed reduction in robot idle time and increased human satisfaction.

Research on bidirectional human-machine interfaces will enable the smooth interaction with roboti... more Research on bidirectional human-machine interfaces will enable the smooth interaction with robotic platforms in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. We complement the gesture-based control by means of a tactile-feedback strategy grounding on a spiking artificial neuron model. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user’s hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pick-and-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the e...

The International Journal of Advanced Manufacturing Technology

The advent of smart manufacturing and the exposure to a new generation of technological enablers ... more The advent of smart manufacturing and the exposure to a new generation of technological enablers have revolutionized the way manufacturing process is carried out. Cyber-Physical Production Systems (CPPS) are introduced as main actors of this manufacturing shift. They are characterized for having high levels of communication, integration and computational capabilities that led them to a certain level of autonomy. Despite the high expectations and vision of CPPS, it still remains an exploratory topic. Multi-Agent Systems (MAS) have been widely used by software engineers to solve traditional computing problems, e.g., banking transactions. Because of their high levels of distribution and autonomous capabilities, MAS have been considered by the research community as a good solution to design and implement CPPS. This work first introduces a collection of requirements and characteristics of smart manufacturing. A comprehensive review of various research applications is presented to underst...

2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT

Sensors and human machine interfaces for collaborative robotics will allow smooth interaction in ... more Sensors and human machine interfaces for collaborative robotics will allow smooth interaction in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user's hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pickand-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the effectiveness of a neuronal spiking model for encoding hand displacement and exerted forces in order to promote a fluid embodiment of the haptic interface and control strategy. The main contribution of this paper is in presenting a robotic arm under gesture-based remote control with multisensory telepresence, demonstrating for the first time that a spiking haptic interface can be used to effectively deliver on the skin surface a sequence of stimuli emulating the neural code of the mechanoreceptors beneath.