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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Juan Jose Garcia Cardenas Xiaoxuan Hei Adriana Tapus ENSTA Paris Institut Polytechnique de Paris Paris France Autonomous Systems and Robotics Lab/U2IS ENSTA Paris Institut Polytechnique de Paris Paris France

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Teleoperated robots, especially in hazardous environments, integrate human cognition with machine efficiency, but can increase cognitive load, causing stress and reducing task performance and safety. This study examines the impact of the information available to the operator on cognitive load, physiological responses (e.g., GSR, blinking, facial temperature), and performance during teleoperation in three conditions: C1 - in presence, C2 - remote with Visual feedback, and C3 - remote with telepresence robot. The findings from our user study involving 20 participants show that information availability significantly impacts perceived cognitive load, as evidenced by the differences observed between conditions in our analysis. Furthermore, the results indicated that blinking rates varied significantly among the conditions. The results also underline that individuals with higher error scores on the spatial orientation test (SOT), reflecting lower spatial ability, are more likely to experience failure in conditions 2 and 3. The results show that information availability significantly affects cognitive load and teleoperation performance, especially depth perception of the robot’s actions. Additionally, the thermal and GSR data findings indicate an increase in stress and anxiety levels when operators perform conditions 2 and 3, thus corroborating an increase in the user’s cognitive load.

关键词： Temperature measurement Visualization Temperature distribution Telepresence Anxiety disorders Cognitive load Physiology Thermal loading Robots system analysis and design

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Factors Influencing Emotional Driving: Examining the Impact of Arousal on the Interplay between Age, Personality, and Driving Behaviors

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SSRN 2024年

作者： Shangguan, Zhegong Han, Xiao El Mrhasli, Younesse Lyu, Nengchao Tapus, Adriana Autonomous Systems and Robotics Lab U2IS ENSTA Paris Institut Polytechnique de Paris 828 Boulevard des Maréchaux Île-de-France Paris91120 France Beijing Jiaotong University Haidian Beijing100044 China Wuhan University of Technology Hongshan Hubei Wuhan430062 China

Drivers' emotions have been widely investigated in transportation for their significant effects on driving behaviors and traffic accidents. Appraisal theory posits that emotional reactions are influenced by individuals' attitudes toward current circumstances and events. Furthermore, individual differences and personality traits lead to different driving attitudes and styles. As a result, it is essential to investigate whether individual differences persist in driving attitudes and styles under the influence of arousal. This study aims to explore the impact of age, personality, and driving experience on driving behaviors. Furthermore, we investigated the interaction effect between different human factors, especially the role of emotional arousal in these interactions. Moderated moderation analysis and moderated mediation analysis were employed to examine how these individual factors interact with one another and influence driving behaviors, including acceleration, speed stability, and steering performance. Moreover, the variation of these interactions under different arousal levels was observed. We used data collected from a driving simulation experiment involving 40 Chinese participants in various emotional states. Our findings revealed that higher-age drivers and experienced drivers displayed lower maximum acceleration and better speed stability. Extraversion was found to have a significant mediation effect on the relationship between age and driving behaviors, and the relation was moderated by arousal states. Moreover, Neuroticism moderated the relationship between driving experience and driving behaviors. In conclusion, this study unveiled how individual factors influence the trajectory of personality development in relation to driving behaviors. These observations indicate that further long-term and individual studies on this topic would be valuable. © 2024, The Authors. All rights reserved.

关键词： Behavioral research

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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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SRG3: Speech-driven Robot Gesture Generation with GAN

SRG3: Speech-driven Robot Gesture Generation with GAN

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International Conference on Control, Automation, robotics and Vision (ICARCV)

作者： Chuang Yu Adriana Tapus Autonomous System and Robotics Lab/U2IS ENSTA Paris Institut Polytechnique de Paris Palaiseau France

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

The human gestures occur spontaneously and usually they are aligned with speech, which leads to a natural and expressive interaction. Speech-driven gesture generation is important in order to enable a social robot to exhibit social cues and conduct a successful human-robot interaction. In this paper, the generation process involves mapping acoustic speech representation to the corresponding gestures for a humanoid robot. The paper proposes a new GAN (Generative Adversarial Network) architecture for speech to gesture generation. Instead of the fixed mapping from one speech to one gesture pattern, our end-to-end GAN structure can generate multiple mapped gestures patterns from one speech (with multiple noises) just like humans do. The generated gestures can be applied to social robots with arms. The evaluation result shows the effectiveness of our generative model for speech-driven robot gesture generation.

关键词： Robots Gallium nitride Three-dimensional displays Generative adversarial networks Generators Decoding Speech processing

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Optimization-Based Control Allocation for Driving/Braking Torque Vectoring in a Race Car

Optimization-Based Control Allocation for Driving/Braking To...

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American Control Conference

作者： Moad Kissai Bruno Monsuez Xavier Mouton Adriana Tapus Department of Computer and System Engineering (U2IS) Institut Polytechnique de Paris ENSTA Paris Autonomous Systems and Robotics Lab Palaiseau France Chassis Systems Department Group Renault Guyancourt France

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

Most of recent researches on the automotive field focus on autonomous vehicles. These vehicles are equipped with conventional chassis systems. The goal is to control the vehicle's traction, brakes, and front steering. This paper discusses the importance of advanced chassis systems, as driving/braking torque vectoring, for both autonomous and non-autonomous vehicles, especially in a race mode. Reliable co-simulation results show that expanding the vehicle's potential leads to high performances and safety with respect to severe situations when optimal control allocation is ensured. Therefore, future passenger cars shall not only be equipped with additional sensors, but also by advanced systems along with adequate control algorithms.

关键词： Tires Torque Mathematical model Force Automobiles Wheels Resource management

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Detecting deception in HRI using minimally-invasive and noninvasive techniques

Detecting deception in HRI using minimally-invasive and noni...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： David-Octavian Iacob Adriana Tapus Autonomous System and Robotics Lab/U2IS Institut Polytechnique de Paris 828 Blvd des Marechaux Palaiseau France

Our work focuses on detecting deception in Human-Robot Interactions (HRI) by using measurement techniques that are appropriate for such interactions. In our previous research works, we obtained interesting results by using thermal and RGB-D cameras. In this paper, we approached this aspect from a different angle and used a lab-designed armband to accurately measure the participants' heart rate and skin conductance. We also developed a deception card game scenario that entices human participants to lie either to a robot or a human game partner, allowing us to monitor and understand the correlations between human physiological manifestations and their trustworthiness. Our results show the existence of statistically significant correlations between the participants' deceptive behaviour and their heart rate, skin conductance, face position, and face orientation. These results allow us to improve robots' ability to detect deception in HRI.

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Human-Robot Team: Effects of Communication in Analyzing Trust

Human-Robot Team: Effects of Communication in Analyzing Trus...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Stefan-Dan Ciocirlan Roxana Agrigoroaie Adriana Tapus Autonomous System and Robotics Lab/U2IS ENSTA Paris Institut Polytechnique de Paris 828 Blvd des Marechaux Palaiseau France

Trust is related to the performance of human teams, making it a significant characteristic, which needs to be analyzed inside human-robot teams. Trust was researched for a long time in other domains like social sciences, psychology, and economics. Building trust within a team is formed through common tasks and it depends on team performance and communication. By applying an online game based tasks for human-robot teams, the effects of three communication conditions (communication without text and verbal interaction, communication with text and verbal interaction related/not related to the task) on trust are analyzed. Additionally, we found that the participants' background is linked to the trust in the interaction with the robot. The results show that in a human-robot team the human trust will increase more over time when he/she is working with a robot that uses text and verbal interaction communication related to the task. They further suggest that human trust will decrease to a lower extent when the robot fails in doing the tasks if it uses text and verbal communication with the human.

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Extensible Control Architecture for Over-Actuated Vehicles

Extensible Control Architecture for Over-Actuated Vehicles

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International Conference on Control, Automation and systems ( ICCAS)

作者： Moad Kissai Xavier Mouton Bruno Monsuez Adriana Tapus Autonomous Systems and Robotics Lab U2IS ENSTA Paris Institut Polytechnique de Paris 828 boulevard des Marchaux Palaiseau France Group Renault Guyancourt France

Most of today's passenger cars are over-actuated. This over-actuation is expected to grow going towards self-driving cars. However, the necessary systems that would be needed for a safe and a comfortable autonomous driving remain uncertain. This paper aims to provide an extensible control architecture that does not depend on a particular system combination. Car manufacturers tend to develop ad hoc rule-based strategies for a specific set of integrated systems. Through several realistic scenarios, we have shown that the control architecture proposed in this paper can be adopted for different set of integrated systems. A minimal effort is required from the control designer when changing the nature of the systems integrated to adapt the control strategy. The control architecture proposed in this paper can serve as a starting point for the standardization of control architectures for future vehicles motion control.

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Crowd sourcing ‘approach behavior’ control parameters for human-robot interaction

Crowd sourcing ‘approach behavior’ control parameters for ...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： François Ferland Adriana Tapus Autonomous Systems and Robotics Lab U2IS ENSTA Pari sTech Université Paris-Saclay France

For service robots to be well received in our daily lives, it is desirable that they appear as friendly as possible rather than some unfriendly characters. While a robot's physical appearance influences this perception, its behavior also has an impact. In order to be sure that a specific robot behavior will be correctly perceived, we propose to its potential users to shape the robot's behavior. In this paper, a specific behavior, “approaching a person”, is evaluated with a Robosoft Kompaï robot. To avoid logistics issues associated with having large groups of novice users performing demonstrations on a physical robot, a web-based approach built around a simulation of the actual robot is proposed. The relationship between the robot and the person is described by the two dimensions of the interpersonal circumplex: communion (hostile or friendly) and agency (submissive or dominant). The users can adjust three parameters of the approach behavior (i.e., distance, trajectory curvature, and deceleration) in a manner that corresponds the best to the described relationship. An analysis of the data from 69 users is presented, along with a verification experiment done with 10 participants and the real robot. Results suggest that users associate hostile robots with straight trajectories, and submissive robots with smoother deceleration.

关键词： Trajectory Analysis of variance Human-robot interaction Service robots Shape

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