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Les notes de cours de L3 MIAGE sur l’introduction à la comptabilité

Introduction à la comptabilité

Présentation pédagogique et synthétique de ce que vous avez appris en lisant la littérature scientifique concernant un problème de recherche,    

1 - définir la problématique qui vous intéresse

2 - Votre état de l’art pourra –entre autres : révéler des verrous, des controverses, des tendances, des erreurs communes, des problèmes ouverts, des théories faisant l’objet de débat, des opportunités de transfert de technologie, etc. 

Un état de l'art rassemble et étudie des travaux choisis issus de la littérature scientifique

articles publiés dans des revues scientifiques et actes de conférences scientifiques (voir la section ‘’sources’’).  

former votre propre théorie, ce faisant vous aussi pourrez apporter votre propre réponse à la question de recherche choisie. 

L’objectif principale de votre mémoire est donc de

 réaliser un analyse critique, rigoureuse et structurée de la littérature scientifique sur une question de recherche.

Afin d’identifier ces articles, vous pouvez :

définir – avec l’aide de votre encadrant, les « mots-clés » qui serviront à réaliser les recherches sur les moteurs et bibliothèques digitales (cf ci-dessous).

Itérer : en cours de recherche, de nouveaux mots-clés (synonymes, autres expressions, autres combinaisons de mots... en français, en anglais) apparaissent régulièrement et doivent être utilisés pour de nouvelles recherches.

Procéder de proche en proche : chaque article possède une section ‘’références’’ qui pointe sur des articles scientifiques qui peuvent eux aussi vous intérésser.

  Il faut absolument veiller à citer vos sources. Pour cela, vous pouvez utiliser le 

 pour citer proprement les sources trouvées : 

How can digital twins be utilized to enhance human-like movements and behaviors in humanoid robotics?

(TITLE-ABS-KEY("digital twin") OR TITLE-ABS-KEY("twin model") OR TITLE-ABS-KEY("digital replica"))

(TITLE-ABS-KEY("humanoid robot") OR TITLE-ABS-KEY("human-like movement") OR TITLE-ABS-KEY("human-robot interaction") OR TITLE-ABS-KEY("robot behavior"))

Title : Systems of Digital Twins and Physical Systems: Interoperability, Decentralization, and Mobility in Robotic Applications

Abstract: Whereas digital twins are receiving an increasing attention, their implementation has been predominated by monolithic and static solutions. A resulting issue is the lack of a modular integration and seamless interplay of digital twins when it comes to adapt and support varying industrial and societal applications. Another drawback arises from limited services that digital twins can provide as the physical system is extended with new components and/or separated from constituting parts, giving rise to a metamorphosic system of systems. Furthermore, the respective mobility of physical systems and citizens assumed to interact with them via their digital surrogates is hardly transformed into industrial and societal opportunities, such as a pervasive and itinerant human-robot-interaction ($\pi$-HRC). Within the scope of our Metarobotics framework that propels $\pi$-HRC, we address these challenges by leveraging on the OPCUA standard to develop portable data connectors that move with and give access to the data source, which is the associated physical system. Our Raspberry-Pi driven connector encapsulates a digital twin of the corresponding system and its offered services to capture the loose coupling and decentralization of systems of systems even remotely and in motion. Each data connector semantically interoperates with any OPC-UA capable system and device via wireless communication. This opens up new opportunities for different monitoring (and control) modalities of large-scale systems whose physical or/and virtual constituting subsystems are distributed across distinct geographical locations in the industrial and societal realm. We apply our framework to a mobile multi-arm robotic system with edge-computing capabilities and demonstrate the performance of its monitoring functionality from the cabin of a moving train in city traffics in practice. We provide experimental measurements results and highlight the usefulness and effectiveness of our approach.

Title : A System for Retargeting Human Motion to Robot with Augmented Feedback via a Digital Twin Setup

Author: Jinhhao Ng, C. K. Quah, Ren Tsong Chua, Budianto Tandianus

Abstract: This paper introduces a human-robot-interaction approach for a robot to learn complex automated tasks via natural human actions. Our system comprises of marker-less human pose estimation that is retargeted onto a robot for it to learn for demonstration (LfD) while incorporating augmented visual feedback to the human. This is done through a digital twin setup comprising of the virtual environment that is a replica of the physical scene with the robot on one end and the human teleoperator on the other. The system begins with a low-cost off-the-shelf marker-less human capture module before its posture is mapped across to the robot via its virtual digital twin. Our mapping takes into account the difference between the human and robot joints by normalization of the Euclidean among the joint lengths. Also, we have included a preliminary adaptive hysteresis thresholding method to overcome potential jittering problem in precision of joint location during motion capture while preserving the high frequency movements. Finally, our system is integrated with state-of-the-art 3D scene reconstruction and object detection methods.

Title : A Digital Twin-Based Large-Area Robot Skin System for Safer Human-Centered Healthcare Robots Toward Healthcare 4.0

Author: G Yang, Z Ye, H Wu, C Li, R Wang, D Kong

Abstract: The fourth revolution of healthcare technologies, i.e., Healthcare 4.0, is putting robotics into human-dominated environments. In such a context, one of the main challenges is to develop human-centered robotics technologies that enable safe and reliable human-robot interaction toward human-robot symbiosis. Herein, robot skin is developed to endow healthcare robots with on-body proximity perception so as to fulfill the promise of safe and reliable robotic systems alongside humans. The sensing performance of the robot skin is evaluated by extensive experiments, providing important guidance on its effective implementation into a specific robot platform. Results show that the developed robot skin has a detection range of 0-50 mm, a maximum sensitivity of 0.7 pF/mm, a minimum resolution of 0.05 mm, a repeatability error of 6.6\%, a hysteresis error of 7.1\%, and bending durability of 2000 cycles. The robot skin is further customized and scaled up to form a large-area sensing system on the exterior of robot arms to support functional safety, which is experimentally validated by approaching distance monitoring and reactive collision avoidance. During the validation, the sensing feedback of the robot skin and the motion of the host robot are visualized remotely in the robot digital twin in a real-time manner via a cloud server. The cloud-based monitoring interface bridges the gap between local healthcare robots and remote professionals, illustrating promising applications where professionals monitor the robot state and intervene in challenging situations to provide instant support for emergent safety issues in human-robot interaction.

Title : Digital Twin based Test- and Verify Framework of Human-Robot Collaboration Solutions

Author: C He, L Fan, Y Xiao, Z Han, Z Luo, C Ge, L Muyang

Abstract: While human-robot collaboration is emerging as a new paradigm for solving problems in the industrial domain, the lack of suitable testing methods has led to insufficient design feedback and unconvincing safety certifications during deployment, which impede its long-term development. These include insufficient design feedback and unconvincing safety certifications during deployment. Adhering to a human-centric principle, this work analyzes deficiencies in existing standards and testing methodologies for human-robot collaboration testing. By integrating digital twin and AI technologies, a simulation-based testing framework is proposed for human-robot collaboration. AI-generated human factors are introduced in the simulation environment to emulate capabilities of the human-robot collaboration solutions under evaluation across diverse scenarios. This explores corner cases while mitigating equipment and personnel risks inherent in physical testing workflows. Through the exploration of corner cases, this research has discovered that developing human-robot collaboration solutions requires greater attention to human factors, rather than primarily considering electromechanical devices, to ensure operator safety during real-world deployment of human-robot collaboration schemes.

Title : Gesture-driven interaction service system for complex operations in digital twin manufacturing cells

Abstract: Industry 5.0 emphasises collaborative work between humans, advanced technology, and artificial intelligence robots, focusing on human-centric principles and integrating flexibility and sustainability to enhance workflows. The advancement of human-robot interaction services can significantly improve the operations efficiency of digital twin manufacturing cells. Motivated by the above background, a gesture-driven interaction architecture for digital twin manufacturing cells is proposed, including data acquisition layer, data processing layer, and application service layer. Secondly, deep learning algorithms are employed for recognising predefined gestures. An improved YOLOv5 algorithm is used to solve the problem of low accuracy in static gesture recognition; while a 3D-CNN-based multimodal data fusion algorithm is used to solve the problem of continuity, diversity, and dimensionality in dynamic gesture recognition. Ultimately, the prototype system is developed utilising Kinect 2.0 and Unity 3D, which involves linking the gesture recognition to the digital twin model, and linking the digital twin model to the physical manufacturing cells. This study is expected to provide theoretical and practical insights to empower human-robot interaction technology in manufacturing cells.

Title : AR-enhanced digital twin for human–robot interaction in manufacturing systems

Abstract: The integration of advanced technologies into manufacturing processes is critical for addressing the complexities of modern industrial environments. In particular, the realm of human–robot interaction (HRI) faces the challenge of ensuring that human operators can effectively collaborate with increasingly sophisticated robotic systems. Traditional interfaces often fall short of providing the intuitive, real-time interaction necessary for optimal performance and safety. To address this issue, we introduce a novel system that combines digital twin (DT) technology with augmented reality (AR) to enhance HRI in manufacturing settings. The proposed AR-based DT system creates a dynamic virtual model of robot operations, offering an immersive interface that overlays crucial information onto the user's field of vision. This approach aims to bridge the gap between human operators and robotic systems, improving spatial awareness, task guidance, and decision-making processes. Our system is designed to operate at three distinct levels of DT functionality: the virtual twin for in-situ monitoring, the hybrid twin for intuitive interaction, and the cognitive twin for optimized operation. By leveraging these levels, the system provides a comprehensive solution that ranges from basic visualization to advanced predictive analytics. The effectiveness of the AR-based DT system is demonstrated through a human-centric user study conducted in manufacturing scenarios. The results show a significant reduction in operational time and errors, alongside an enhancement of the overall user experience. These findings confirm the potential of our system to transform HRI by providing a safer, more efficient, and more adaptable manufacturing environment. Our research contributes to the advancement of smart manufacturing by evidencing the synergistic benefits of integrating DT and AR into HRI.

Title : Human-Cyber-Physical System for Industry 5.0: A Review From a Human-Centric Perspective

Author: Shanhe Lou, Zhongxu Hu, Yiran Zhang, Yixiong Feng, Mengchu Zhou

Abstract: Industry 5.0 heralds a new wave of the industrial revolution, placing a spotlight on human-centric intelligent manufacturing. At the core of Industry 5.0 lies the human-cyber-physical system (HCPS), a composite intelligent system where interactions among humans, cyberspace, and physical assets are orchestrated across diverse manufacturing levels and phases. Understanding the pivotal roles played by humans in these advanced systems is of paramount importance. Nonetheless, the exploration of HCPS within the context of Industry 5.0 remains in its infancy. This paper presents a holistic literature review of industrial HCPS from a human-centric perspective. A united architecture is employed to encompass the aspects of cognitive-to-technology integration and human-to-human interaction in HCPS, highlighting human-in-the-loop, human-on-the-loop, and human-in-the-society paradigms. The mechanisms of these paradigms and their effects on design, production, and service are investigated to expand the research landscape of intelligent manufacturing in Industry 5.0. Key enabling technologies that facilitate harmonious tri-space integration are introduced, and the future challenges of industrial HCPS are discussed. This work is expected to attract more open discussions and in-depth research on HCPS in the new industrial revolution era. \textlessitalic\textgreaterNote to Practitioners\textless/italic\textgreater\&\#x2014;This paper is motivated by the emergence of Industry 5.0 that integrates humans into cyber-physical systems to offset drawbacks on both sides. It presents an overview of HCPS-related works to identify the state-of-the-art and open problems in the Industry 5.0 era. The review of HCPS applications in the design, production, and service phases can benefit engineers in the intelligent manufacturing area. Key enabling technologies on human ability augmentation, human-robot interaction, digital twin, human-cyber-physical data fusion, crowdsourcing, and system modeling, are analyzed to attract researchers in broader research fields to join in the development of industrial HCPS.

Link : https://www.researchgate.net/profile/Shanhe-Lou/publication/378053098_Human-Cyber-Physical_System_for_Industry_50_A_Review_From_a_Human-Centric_Perspective/links/66a8b3f14433ad480e8498c9/Human-Cyber-Physical-System-for-Industry-50-A-Review-From-a-Human-Centric-Perspective.pdf

Title : Mind the gap: towards building a more seamless sim-to-real platform for robotic grasping and manipulation

Author: Z Zhang, H Wang, L Zhou, Z Liu, C Liu, FEH Tay, WF Lu, MH Ang Jr

Abstract: This paper presents a vision of creating a more seamless sim-to-real robotic grasping and manipulation platform, bridging the gap between simulated environments and real-world applications. In recent years, the emergence of digital twin technology has revolutionized how we develop and test such applications. A digital twin can simulate the behavior of a physical system in a virtual replica of the real-world environment in real-time, enabling engineers and researchers to conduct detailed analysis and evaluation before deploying robotic systems in the real world. In this paper, we study the potential of creating a digital twin that allows researchers and engineers to seamlessly deploy a grasping system trained on synthetic data and tested in a simulation environment without writing any additional code or doing additional calibration. Using our proposed platform, we present a case study done using a robotic grasping algorithm and analyze the advantages and limitations of our current platform. In the end, we suggest some possible improvements and future directions to enhance the platform's effectiveness and applicability.

Title : Creating a Digital Twin of the ABB YuMi Robot to Improve the Human-Robot Interaction Experience

Author: V Andrusyshyn, I Andrusyshyn, K Židek, V Ivanov, J Piteľ, J Trojan

Abstract: This work is devoted to creating a digital twin of the ABB YuMi industrial robot to improve the user experience of interacting with the robot during the collaborative assembly process. The digital twin will be used to provide visual feedback that includes the current state of the robot (including position, movement speed, type of current operation, overall program structure, etc.) and displays the robot's intentions (type of next operation, current robot trajectory, etc.). Greater awareness of the system's operation will allow a person to focus on production tasks, thereby increasing production efficiency. Unreal Engine was used to create the digital twin. Although this gaming engine was developed with a focus on creating games, it is still promising for use in the industrial environment - its high popularity contributes to its active development and the introduction of the most modern capabilities and optimizations for working with 3D objects, including improved physics.

Title : Remote Monitoring and Control of Mobile Robots in Real-Time Using Multimodal Digital Twins

Abstract: Although digital twins have been playing a pivotal role in the management of the lifecycle of physical robotic systems of systems, they have hardly been employed to actively guide mobile robots in real-time. In fact, the guidance of such systems requires functionalities, including the perception of environmental constraints and avoidance of collisions. A spatial information stream beyond the internal robot state measured using proprioceptive sensors is therefore needed. Exteroceptive sensors help meet this demand. Nevertheless, such sensors have received little attention thus far in the development of digital twins. On the other hand, various mobility objectives, such as reverse motions, might require the awareness of the historical internal state of the distant robot. For instance, the current energy budget is likely to constrain the reachability of the initial robot location, even when spatially and kinematically feasible. We therefore develop a web-based framework to monitor and actively steer mobile robots while leveraging on multimodal digital twins. We collect data about the internal state and camera-captured neighborhood of the robot in real-time. The robot operator is thereby provided with an enriched digital model of the internal dynamics and environmental perception of the robot. This elevates situational awareness and facilitates decision support. We then develop a versatile graphical interface that helps holistically monitor and actively steer the mobile robot. Since the multi-modal and bidirectional approach is intuitive and device-agnostic, even novices can remotely guide the robot on mobile phones from everywhere. We show the usefulness and effectiveness of our approach in use-case scenarios in practice.

Title : Enhancing human-guided robotic assembly: AR-assisted DT for skill-based and low-code programming

Abstract: Efficient and natural programming strategies play a crucial role in enabling human-guided robotic assembly to adapt quickly to dynamic tasks. The combination of Augmented Reality (AR) and Digital Twins (DT) has shown promising potential in enhancing the intuitiveness of human–robot interaction while leveraging digital representations of human intelligence to empower robots in manufacturing tasks. However, traditional programming methods lack intuitive interaction and rely heavily on simulation environments or pre-set CAD models, leading to high costs for both initial setup and sim-to-real deployment. On the other hand, existing AR-based robot control methods have primarily focused on the basic movements of robots, overlooking higher-level skills necessary for complex tasks. To address these limitations, this study introduces a four-layer system architecture that integrates AR-assisted DT into skill-based robotic assembly scenarios. Additionally, a skill-based and low-code programming system for human-guided robotic assembly is designed and implemented, which incorporates natural human guidance and robot autonomous intelligence to generate adaptive and feasible action plans. The feasibility and efficiency of the proposed system are verified by two case studies and a quantitative experiment comparing to traditional programming methods. The results demonstrate the usability of our AR-assisted DT approach in improving programming efficiency, intuitiveness, and safety for human-guided robotic assembly while reducing cognitive load.

Link: https://pdf.sciencedirectassets.com/277340/1-s2.0-S0278612524X00035/1-s2.0-S0278612524000827/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEDcaCXVzLWVhc3QtMSJGMEQCIHuOamleSoDvPWhQrPyFtL7tRAyK8Bc8y2%2BTQNj%2BlIIDAiBsR9Mcfy%2FVR8s3DUCxGnE68JVUT1I9yd9it0XaEe9MhCq7BQjA%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F8BEAUaDDA1OTAwMzU0Njg2NSIMWz0YyE45cvjIRSFpKo8F0NHMztUxJdfkGwtQudxGdISAzvZCi4cSFAzp86Hxl13m0b3ZKcx1Gqv8Qf8CMCCUVvfOGNNego0XGpWaSqHxhMX9oQSxHuYWywQ4G8QCITNcigWRr5YsiIYab23z1IJA5%2BKWR3CbSeI%2FTtRiDUuebbcwX7NMyFgUex%2FRSIetXbgnm7TzgtKNziGqZY%2FoGPJtTTx7jkPW%2FVQaTwYp8pCPL8DFpspGmsf%2BWMPxCkZ2qdAy6E0MAfqgL6RNfOKAkfUgDpIEQAlzq%2FGc3BddEq5u9OaF2wvkHlJqjA12qcqGA%2Fk3agr%2B8GxPqWrm9W2ZwcflD81fFI%2FIivsHqMxmY%2BvxnAcK3icNF2NZS4y7D5JZqgF%2FFZXA7v%2FKPYsXsaqNkSDZfRi0P4ft8yx5dwWJEQt5f9d34uBVtoADLsRSvAiuBQNVU1kzjDRfzqS8ZXIIU1mFLvfr3v3Wpx6mdhjVCcKuqJ87scurzXWzeQceKZROPOfppgKo4fXIDfhhLggxMLLJpNHJ938IcUhqixMGS%2FhPRCEt07fmw%2FHeVjDN9SmAfH0rMdf%2F84FPnFSaQzj7O7HT%2F9xiJNh5epDfCp6J9rl7mhPAhu2DEpwXcG5vXE4lX4YuGdQQKfAqZolvqtehOKiyUm0zbvtDFECbT9Bf35Cl6qam%2BEEF2Ak7jkTBolYkhWsVhl%2BwRtZ8Hv37f%2BTNkZmaBeb5iZlXQvnzT4nvATOYUcfO9LXZOQk3qjCk29dlS1gtLdfClrkmYpl9mrJg%2FiIbHaVZ4iVmTthXjZ%2Fm7UCpGGaptpwzHQV1Fl08Kf3IbUQD%2B5OelHIfjXGIrav%2FfdVUB%2B0QeYNJ2%2BttvXOh4zGDwgJs8zTkMRilm6KxneRKTTCCzc25BjqyAQo3XnAw25y1adSAIFGzefqiVQS6jIPMP09NsB%2F0d8UW%2FyoD4aGdgKathfUiyeW%2BJ592ogSDolLpD9Fl2VUTuLmVZ%2Fdv2mlrr3HLU%2FFSZ8cFmKFR8nFtVIXfyttwtlsEtw09pt4R%2Bg5vgR0Yl3GscD6OZVfYj%2FtSoqStW3%2Bf3mWs5GrDq%2Bfcoh8qffyNcbyEHLXiWu55J4fvlDSKQ43RMpWy1kwWTHiGp4qfqJK6BsAIPVA%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20241112T151718Z&X-Amz-SignedHeaders=host&X-Amz-Expires=300&X-Amz-Credential=ASIAQ3PHCVTYZWG66Z2R%2F20241112%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=5e9449fcb9841d7e06b0d0c298013362ba220977836d6eb0efabe63ffd596e4e&hash=57edc540c97e18707df9456952cb3d1288000a04a75df5279991d9607a6dfb29&host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&pii=S0278612524000827&tid=spdf-c01f82b5-cd63-48d4-bbdd-523e696e18e9&sid=65f5cae92522e84b015bb390ad2f722a80c9gxrqb&type=client&tsoh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&ua=00105f035e5057070252&rr=8e177cf4e832d479&cc=fr

Title : Beyond simulation: Unlocking the frontiers of humanoid robot capability and intelligence with Pepper's open-source digital twin

Author: H Sekkat, O Moutik, B El Kari, Y Chaibi, TA Tchakoucht, AEH Alaoui

Abstract: This research paper presents a high-fidelity, open-source digital-twin of the Pepper robot developed within the framework of the Robot Operating System 2 (ROS 2) for better simulation realism in complex tasks of machine learning. We developed a dedicated, custom ROS 2 package with modern simulation tools, such as Gazebo Sim, MoveIt 2, Rviz2, that brings complete, realistic environments in line with the exact behaviors and interactions of robots in reality. Better accuracy of the physical movement of Pepper robot's simulation was shown on the digital twin, validated by the Choregraphe software and real robot performance, to be a strong platform of collaboration and further research by the community. This development greatly pushes the envelope of human-like humanoid robotics further by offering a scaled, flexible, and plausible training environment conducive to integrating complex algorithms of robot learning and interaction capabilities.

Link : https://www.cell.com/action/showPdf?pii=S2405-8440%2824%2910487-2

Title : Subtractive manufacturing of composite materials with robotic manipulators: a comprehensive review

Abstract: Robotic manipulators play an innovative role as a new method for high-precision, large-scale manufacturing of composite components. However, machining composite materials with these systems presents unique challenges. Unlike traditional monolithic materials, composites exhibit complex behaviour and inconsistent results during machining. Additionally, robotic manipulator as a machine tool often associates with stiffness and vibration issues which adds another layer of complexity to this approach. By employing a comprehensive analysis and a combination of quantitative and qualitative review methodology, this review paper aims to survey diverse properties of composite materials by different categories and their interaction with machining processes. Subsequently, a survey of manufacturing techniques for composite machining following with a review in various modeling practices to capture material machining behaviour under a systematic framework is presented. Thereafter, the reviewed literature examines the errors inherent in robotic systems, alongside ongoing research efforts in modeling to characterise robot behaviour and enhance its performance. Afterward, the paper explores the application of data-driven modelling methods, with a primary focus on digital twins, in enabling real-time monitoring and process optimisation. Finally, this paper aims to identify the gap in this field and suggests the potential routes for future research and application as well as their challenges.

Link : https://link.springer.com/article/10.1007/s00170-024-14427-5

Title : Safe-By-Design Digital Twins for Human-Robot Interaction: A Use Case for Humanoid Service Robots

Author: J Škerlj, M Hamad, J Elsner, A Naceri, S Haddadin

Abstract: Integrating humanoid service mobile robots into human environments presents numerous challenges, primarily concerning the safety of interactions between robots and humans. To address these safety concerns, we propose a novel approach that leverages the capabilities of digital twin technology by tailoring it to incorporate comprehensive and robust safety concepts. This paper introduces a "safe-by-design"digital twin that operates alongside the real twin robot in the loop, engaging real-time safety framework during physical interactions with the surrounding environment, including humans.To validate the effectiveness of our proposed safe-by-design digital twin framework, we conducted experiments using a humanoid service mobile robot alongside simulated human counterparts. Our results demonstrate the capability of the integrated impact safety module within the proposed digital twin approach to limit the velocities of both the robot's base and arms, adhering to injury biomechanics-based safety thresholds. These findings emphasize the promise of our proposed approach for ensuring the physical safety of humanoid service mobile robots operating in dynamic human environments. It enables the digital twin to preemptively identify potential safety hazards and formulate safe intervention actions to ensure the robot's compliance with safety regulations, paving the way for safer and more widespread adoption of robotic systems in various service domains.

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