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检索条件"机构=U2IS - Computer Science and System Engineering Laboratory"

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systems engineering and Robotics : A Survey

Systems Engineering and Robotics : A Survey

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Annual IEEE systems Conference

作者： Thomas Rigaut Omar Hammami U2IS - Computer Science and System Engineering Laboratory ENSTA Paris Polytechnique Institute of Paris Palaiseau France

ISBN: (数字)9798331508180

ISBN: (纸本)9798331508197

The systems engineering and robotics communities evolve in parallel, although they share common concepts and related issues. This article proposes a state-of-the-art of publications tackling both systems engineering (SE) and Robotics, to identify added value of systems engineering for Robotics, and lessons learnt for systems engineering from robotics use cases. In the framework of the systems engineering community, this synthesis of works from academics, industrial and government agencies should ease the building of SE-based seamless integrated framework for architecture, design, verification and validation of heterogeneous swarms of collaborating unmanned ground vehicles and unmanned aerial vehicles.

关键词： Surveys Knowledge engineering Service robots Architecture systems engineering and theory Autonomous aerial vehicles Land vehicles systems engineering education Modeling system of systems

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system of systems Architecture and Autonomous Robot Swarms: A Long Awaited Junction

System of Systems Architecture and Autonomous Robot Swarms: ...

引用

Annual IEEE systems Conference

作者： Thomas Rigaut Omar Hammami U2IS - Computer Science and System Engineering Laboratory ENSTA Paris Polytechnique Institute of Paris Palaiseau France

ISBN: (数字)9798331508180

ISBN: (纸本)9798331508197

Research on the design of autonomous robot swarms has explored many directions over the past ten years (multi-robot systems, coordination protocols, biomimicry, centralized or distributed architecture) but has struggled to combine these different axes in a holistic design approach. The junction between autonomous robot swarm engineering and systems of systems engineering must be pushed further. The first step is to evaluate the contribution of systems of systems architecture to the design of autonomous robot swarms. We propose two initial tests of the relevance of this approach: do the methods and languages of systems of systems architecture allow us to describe the dynamics of these autonomous robot swarms? Do the concepts of system of systems architecture allow us to establish a taxonomy of autonomous robot swarms? This approach should also allow us to test the current limits of the standards of system of systems architecture: taxonomies too focused on the governance of systems of systems, and coexistence without unification of numerous static architecture methods (Model-Based systems engineering, Architecture Frameworks, Hypergraphs, etc.) and dynamic architecture methods (Dynamical systems, system Dynamics, State Machine Diagrams, Event-B modeling, Agent-Based Modeling, BPMN, Activity Diagrams, etc.)

关键词： Protocols system dynamics Taxonomy Multi-robot systems Modeling Junctions Dynamical systems Standards system of systems Autonomous robots

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Multi-objective Optimisation of RISC-V CV32A6 for ML application

Multi-objective Optimisation of RISC-V CV32A6 for ML applica...

引用

IEEE International Symposium on Embedded Multicore Socs (MCSoC)

作者： Bastien Hubert Omar Hammami Computer Science and Systems Engineering Laboratory (U2IS) ENSTA Paris Palaiseau France

RISC-V architectures are rapidly gaining in popularity in embedded systems, in which each mW counts. Since AI-related applications such as image recognition or neural networks tend to be highly energy consuming, low-power techniques are required to optimise the autonomy of systems using SoCs to run such ***, the trade-off between energy consumption, application performance and resource use requires a multi-objective optimisation with a potentially very important number of optimisation parameters to be performed on the SoC. As they rely on heuristics that are likely to only return locally optimal solutions, empirical methods must be *** address this issue, a technology-agnostic mathematical model is introduced to represent how optimisations are applied to a SoC, and a workflow designed to perform an intelligent exhaustive exploration of the optimisation space has been developed to highlight a subset of optimal processor *** of the ARIANE/CV32A6 RISC-V processor, running a CNN propagation on a Xilinx Zynq 7020 FPGA, has shown very encouraging results using low degree configurations, and is likely to perform even better with higher degree configurations.

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Multi-objective Optimisation of RISC-V CV32A6 for ML application

Multi-objective Optimisation of RISC-V CV32A6 for ML applica...

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IEEE International Conference on Design & Test of Integrated Micro & Nano-systems (DTS)

作者： Bastien Hubert Omar Hammami Computer Science and Systems Engineering Laboratory (U2IS) ENSTA Paris Palaiseau France

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Exploring Help-Seeking Behavior, Performance, and Cognitive Load in Individual Tutoring: A Comparative Study between Human Tutors and Social Robots

Exploring Help-Seeking Behavior, Performance, and Cognitive ...

引用

IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Xiaoxuan Hei Heng Zhang Adriana Tapus Computer Science and System Engineering Department (U2IS) Autonomous Systems and Robotics Lab ENSTA Paris Institut Polytechnique de Paris Paris France

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Social robots have become increasingly prevalent in the context of one-on-one tutoring, serving as effective educational aids. In response to this trend, the present study was devised to conduct a comparative analysis between human tutors and robot tutors. Additionally, the study aims to investigate how varying previous knowledge in robots influence students’ tendencies for help-seeking. By examining the performance and physiological signals of participants, this research seeks to provide valuable insights into the effectiveness of social robots in educational contexts. 21 participants were divided into three groups, each seeking assistance from a human tutor (HT), seeking help from a robot without any prior knowledge of robots (RT1), and seeking help from a robot after gaining some understanding of its capabilities (RT2). Our results demonstrated that participants sought more help from robot than from human and participants in Group RT2 performed better than participants in Group RT1. However, participants experienced greater cognitive load when interacting with a robot tutor compared to interacting with a human tutor. Future work could focus on developing interventions to alleviate students’ cognitive load during interactions with robot tutors.

关键词： Social robots Robot vision systems Cognitive load Market research Cameras Physiology Behavioral sciences Robots Thermal stresses Stress

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Estimating Complexity for Perception-based ADAS in unstructured Road Environments

Estimating Complexity for Perception-based ADAS in Unstructu...

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IEEE Symposium on Intelligent Vehicle

作者： Imane Taourarti Ayesha Choudhary Vivek Kumar Paswan Aditya Kumar Arunkumar Ramaswamy Javier Ibanez-Guzman Bruno Monsuez Adriana Tapus Autonomous Systems and Robotics Lab/U2IS Computer Science and System Engineering (U2IS) ENSTA Paris Institut Polytechnique de Paris France Research Department Renault Group France School of Computer and Systems Sciences Jawaharlal Nehru University New Delhi India

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

Advanced Driver Assistance systems (ADAS) are rapidly becoming a standard feature in modern road vehicles, enhancing safety and driver comfort. As ADAS adoption expands across diverse geographical and cultural regions, the performance of camera-based perception systems may vary significantly due to environmental and expected social behaviour of the different actors. This paper explores the referred factors and evaluates the traffic environment complexity for vehicles with different levels of automation. In particular, we propose a novel modeling and quantitative assessment approach for environment complexity. Specifically, we compare a perception model trained on united States dataset with a dataset from India, a nation characterized by unique traffic patterns, signage conventions, and cultural norms to assess its performance variation, and to lay the basis for proposing influencing factors of traffic environment complexity. We establish a scheme of referential and additional static factors and based on an expert evaluation, environment complexity is established. The effectiveness of the proposed approach is testified by naturalistic driving data. These findings pave the way for future research in intelligent driving and emphasize the importance of addressing cultural nuances as vehicle automation levels increase.

关键词： Measurement Automation Roads Road vehicles Globalization Complexity theory Safety

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Robots in education: Influence of Regulatory Focus Theory

Robots in education: Influence of Regulatory Focus Theory

引用

IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Xiaoxuan Hei Heng Zhang Adriana Tapus Computer Science and System Engineering Department (U2IS) Autonomous Systems and Robotics Lab ENSTA Paris Institut Polytechnique de Paris Paris France

The Covid-19 pandemic has massively developed the use of distance learning. The limits of this practice have gradually come to light, both for students and for teachers. It is now crucial to design alternative solutions to overcome the shortcomings of videoconferencing in terms of involvement, concentration, learning, and equity. Social robots are increasingly used as tutors in the educational context and help improve teaching efficiency. Many psychology-based principles have been applied in education to guide instructional strategies, motivate students, and create a positive and productive learning environment. In this work, we use Regulatory Focus Theory (RFT), which categorizes an individual’s motivation into two types: Promotion and Prevention. Promotion-focused individuals are motivated by the potential for growth and achievement, whereas prevention-focused individuals are motivated by the potential for avoiding negative outcomes. Based on RFT, we aim to explore if and how the regulatory-focused behavior of the tutor robot can affect participants’ learning outcomes. In this work, a language learning scenario was designed with two conditions: (1) a robot tutor with promotion-focused behavior, (2) a robot tutor with prevention-focused behavior. The results are encouraging and support that promotion robot tutor can increase the learning efficiency of promotion participants and prevention robot tutor will enhance the learning interest of prevention participants.

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Robot Laughter: Does an appropriate laugh facilitate the robot’s humor performance?

Robot Laughter: Does an appropriate laugh facilitate the rob...

引用

IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Heng Zhang Xiaoxuan Hei Junpei Zhong Adriana Tapus Computer Science and System Engineering Department (U2IS) Autonomous Systems and Robotics Lab ENSTA Paris Institut Polytechnique de Paris Paris France Department of Rehabilitation Sciences The Hong Kong Polytechnic University Hong Kong

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Laughter serves as a subtle social signal in human interaction, playing an essential role in expressing emotions and facilitating social connections. However, laughter comes in various forms and is usually accompanied by different non-verbal expressions, such as facial expressions and gestures. These accompanying factors can significantly influence the effect of laughter in diverse contexts, thus complicating the research on laughter, especially in understanding its role in social dynamics. Consequently, endowing robots with the ability to appropriately use laughter in interactions with humans is still a big challenge. Our current study focuses on the effect of robot laughter on robot humor expression. Our objective is to investigate whether and how two factors, the type of laughter and the robot laughter gesture, impact the overall humor performance. In this study, we selected four types of laughter (sarcastic, joyful, embarrassed, and relieved laughter) from a laughter corpus based on four specific types of jokes (Affiliative, Aggressive, Self-enhancing, and Self-defeating). For each type of laughter, we designed distinct robot gestures. During the humor performance, the robot NAO delivered jokes accompanied by matching or mismatching laughter, with or without corresponding gestures. To enhance the quantity and diversity of experimental data, we conducted an online survey utilizing recordings of the robot’s humor performance. The experimental findings indicate that when the robot’s laughter matches the type of humor in the joke, participants rate the humor performance significantly higher compared to situations where there is a mismatch. Additionally, the results confirm the positive impact of robot laughter gestures on humor performance.

关键词： Surveys Recording Robots

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Analyzing Data Efficiency and Performance of Machine Learning Algorithms for Assessing Low Back Pain Physical Rehabilitation Exercises

Analyzing Data Efficiency and Performance of Machine Learnin...

引用

European Conference on Mobile Robots (ECMR)

作者： Aleksa Marusic Louis Annabi Sao Mai Nguyen Adriana Tapus Autonomous Systems and Robotics Lab Computer Science and System Engineering (U2IS) ENSTA Paris Institut Polytechnique de Paris Palaiseau France Dep. Informatique IMT Atlantique

Physical rehabilitation focuses on the improvement of body functions, usually after injury or surgery. Patients undergoing rehabilitation often need to perform exercises at home without the presence of a physiotherapist. computer-aided assessment of physical rehabilitation can improve patients' performance and help in completing prescribed rehabilitation exercises. In this work, we focus on human motion analysis in the context of physical rehabilitation for Low Back Pain (LBP). As 2D and 3D human pose estimation from RGB images had made impressive improvements, we aim to compare the assessment of physical rehabilitation exercises using movement data acquired from RGB videos and human pose estimation from those. In this work, we provide an analysis of two types of algorithms on a Low Back Pain rehabilitation datasets. One is based on a Gaussian Mixture Model (GMM), with performance metrics based on the log-Likelihood values from GMM. Furthermore, with the recent development of Deep Learning and Graph Neural Networks, algorithms based on Spatio-Temporal Graph Convolutional Networks (STGCN) are taken as a novel approach. We compared the algorithms in terms of data efficiency and performance, with evaluation performed on two LBP rehabilitation datasets: KIMORE and Keraal. Our study confirms that Kinect, OpenPose, and BlazePose data yield similar evaluation scores, and shows that STGCN outperforms GMM in most configurations.

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Robot self-recognition via facial expression sensorimotor learning

Robot self-recognition via facial expression sensorimotor le...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Zhegong Shangguan Mengyuan Ding Chuang Yu Chaona Chen Adriana Tapus Autonomous Systems and Robotics Lab/U2IS ENSTA Paris Institut Polytechnique de Paris 828 Boulevard des Maréchaux Palaiseau France National Engineering Laboratory for Visual Information Applications college of Artificial Intelligence Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China Cognitive Robotics Lab Department of Computer Science University of Manchester Kilburn Building Oxford Rd Manchester UK School of Psychology and Neuroscience University of Glasgow Glasgow UK

To develop robots that can show cognitive functions, we must learn from the knowledge of human cognition. Existing biological and psychological evidence suggests that self-face perception and sensorimotor learning mechanisms play a crucial role in self-recognition. However, one of the most important self-identity cues – facial information – has not been extensively studied in the robot self-recognition task. Current research on robot self-recognition primarily relies on the recognition of high-precision targets and tracking of manipulator motions, where the self-perception of facial information is not well studied. In this work, we propose a novel approach to achieve self-recognition via self-perception of facial expressions. Specifically, we developed a Conditional Generative Adversarial Network (CGAN) model using the knowledge on human cognitive and sensorimotor functions. It allows the robot to be aware of self-face (i.e., off-line model). Passing the observed visual variations in a mirror and comparing them to self-perceptive information, the robot can recognize the self through an online Bayesian learning regression. The results of our first experiment show that the robot can recognize itself in a mirror. The results from the second experiment show that our algorithm could be tricked by a similar robot with the same facial expressions, which is similar to the rubber hand illusion (RHI).

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