62,715 research outputs found
Regulating Highly Automated Robot Ecologies: Insights from Three User Studies
Highly automated robot ecologies (HARE), or societies of independent
autonomous robots or agents, are rapidly becoming an important part of much of
the world's critical infrastructure. As with human societies, regulation,
wherein a governing body designs rules and processes for the society, plays an
important role in ensuring that HARE meet societal objectives. However, to
date, a careful study of interactions between a regulator and HARE is lacking.
In this paper, we report on three user studies which give insights into how to
design systems that allow people, acting as the regulatory authority, to
effectively interact with HARE. As in the study of political systems in which
governments regulate human societies, our studies analyze how interactions
between HARE and regulators are impacted by regulatory power and individual
(robot or agent) autonomy. Our results show that regulator power, decision
support, and adaptive autonomy can each diminish the social welfare of HARE,
and hint at how these seemingly desirable mechanisms can be designed so that
they become part of successful HARE.Comment: 10 pages, 7 figures, to appear in the 5th International Conference on
Human Agent Interaction (HAI-2017), Bielefeld, German
In good company? : Perception of movement synchrony of a non-anthropomorphic robot
Copyright: © 2015 Lehmann et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Recent technological developments like cheap sensors and the decreasing costs of computational power have brought the possibility of robotic home companions within reach. In order to be accepted it is vital for these robots to be able to participate meaningfully in social interactions with their users and to make them feel comfortable during these interactions. In this study we investigated how people respond to a situation where a companion robot is watching its user. Specifically, we tested the effect of robotic behaviours that are synchronised with the actions of a human. We evaluated the effects of these behaviours on the robotâs likeability and perceived intelligence using an online video survey. The robot used was Care-O-botÂź3, a non-anthropomorphic robot with a limited range of expressive motions. We found that even minimal, positively synchronised movements during an object-oriented task were interpreted by participants as engagement and created a positive disposition towards the robot. However, even negatively synchronised movements of the robot led to more positive perceptions of the robot, as compared to a robot that does not move at all. The results emphasise a) the powerful role that robot movements in general can have on participantsâ perception of the robot, and b) that synchronisation of body movements can be a powerful means to enhance the positive attitude towards a non-anthropomorphic robot.Peer reviewe
Influence of Muscle Fatigue on Electromyogram-Kinematic Correlation During Robot-Assisted Upper Limb Training
© The Author(s) 2020. Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us. sagepub.com/en-us/nam/open-access-at-sage).Introduction: Studies on adaptive robot-assisted upper limb training interactions do not often consider the implications of muscle fatigue sufficiently. Methods: In order to explore this, we initially assessed muscle fatigue in 10 healthy subjects using electromyogram features (average power and median power frequency) during an assist-as-needed interaction with HapticMASTER robot. Spearmanâs correlation study was conducted between EMG average power and kinematic force components. Since the robotic assistance resulted in a variable fatigue profile across participants, a completely tiring experiment, without a robot in the loop, was also designed to confirm the results. Results: A significant increase in average power and a decrease in median frequency were observed in the most active muscles. Average power in the frequency band of 0.8-2.5Hz and median frequency in the band of 20-450Hz are potential fatigue indicators. Also, comparing the correlation coefficients across trials indicated that correlation was reduced as the muscles were fatigued. Conclusions: Robotic assistance based on userâs performance has resulted in lesser muscle fatigue, which caused an increase in the EMG-force correlation. We now intend to utilize the electromyogram and kinematic features for the auto-adaptation of therapeutic human-robot interactions.Peer reviewedFinal Published versio
Collaborative Bimanual Manipulation Using Optimal Motion Adaptation and Interaction Control Retargetting Human Commands to Feasible Robot Control References
This article presents a robust and reliable humanârobot collaboration (HRC) framework for bimanual manipulation. We propose an optimal motion adaptation method to retarget arbitrary human commands to feasible robot pose references while maintaining payload stability. The framework comprises three modules: 1) a task-space sequential equilibrium and inverse kinematics optimization ( task-space SEIKO ) for retargeting human commands and enforcing feasibility constraints, 2) an admittance controller to facilitate compliant humanârobot physical interactions, and 3) a low-level controller improving stability during physical interactions. Experimental results show that the proposed framework successfully adapted infeasible and dangerous human commands into continuous motions within safe boundaries and achieved stable grasping and maneuvering of large and heavy objects on a real dual-arm robot via teleoperation and physical interaction. Furthermore, the framework demonstrated the capability in the assembly task of building blocks and the insertion task of industrial power connectors
How Can Robots Adapt To A Social Human World? A Study Into The Role Gestures Can Play In Human-Robot Relations
There is no doubt that robots are now starting to increasingly be integrated into mainstream society, and as they do the amount of contact and the number of interactions they have with humans will increase at a similar rate. These interactions open a new set of issues for robot designers and programmers. What is the best way for robots to interact with humans? This study tested the importance of gestures in creating effective human-robot interactions. Conducted using the PR2, this study explored the role of gestures in two basic kinds of communications: the robot communicating a need: low power) to an unsuspecting human, and a robot building trust with a human participant on an instruction reading task. We predicted that gestures would lead to more effective interactions than the non-gesture controls. We also used the opportunity to explore a largely unresearched area in proxemics: the idea that loose, ĂąâŹĆbouncingù⏠arms led to lower attributions of dominance than stiff, fixed arms. Our research highlighted the importance of gestures in communication, particularly among people who tended to look at robots as more than machines
Touching a mechanical body: tactile contact with body parts of a humanoid robot is physiologically arousing
A large literature describes the use of robotsâ physical bodies to support communication with people. Touch is a natural channel for physical interaction, yet it is not understood how principles of interpersonal touch might carry over to human-robot interaction. Ten students participated in an interactive anatomy lesson with a small, humanoid robot. Participants either touched or pointed to an anatomical region of the robot in each of 26 trials while their skin conductance response was measured. Touching less accessible regions of the robot (e.g., buttocks and genitals) was more physiologically arousing than touching more accessible regions (e.g., hands and feet). No differences in physiological arousal were found when just pointing to those same anatomical regions. Social robots can elicit tactile responses in human physiology, a result that signals the power of robots, and should caution mechanical and interaction designers about positive and negative effects of human-robot interactions
Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning
Mobility in an effective and socially-compliant manner is an essential yet challenging task for robots operating in crowded spaces. Recent works have shown the power of deep reinforcement learning techniques to learn socially cooperative policies. However, their cooperation ability deteriorates as the crowd grows since they typically relax the problem as a one-way Human-Robot interaction problem. In this work, we want to go beyond first-order Human-Robot interaction and more explicitly model Crowd-Robot Interaction (CRI). We propose to (i) rethink pairwise interactions with a self-attention mechanism, and (ii) jointly model Human-Robot as well as Human-Human interactions in the deep reinforcement learning framework. Our model captures the Human-Human interactions occurring in dense crowds that indirectly affects the robot's anticipation capability. Our proposed attentive pooling mechanism learns the collective importance of neighboring humans with respect to their future states. Various experiments demonstrate that our model can anticipate human dynamics and navigate in crowds with time efficiency, outperforming state-of-the-art methods
Design of an Energy-Aware Cartesian Impedance Controller for Collaborative Disassembly
Human-robot collaborative disassembly is an emerging trend in the sustainable
recycling process of electronic and mechanical products. It requires the use of
advanced technologies to assist workers in repetitive physical tasks and deal
with creaky and potentially damaged components. Nevertheless, when
disassembling worn-out or damaged components, unexpected robot behaviors may
emerge, so harmless and symbiotic physical interaction with humans and the
environment becomes paramount. This work addresses this challenge at the
control level by ensuring safe and passive behaviors in unplanned interactions
and contact losses. The proposed algorithm capitalizes on an energy-aware
Cartesian impedance controller, which features energy scaling and damping
injection, and an augmented energy tank, which limits the power flow from the
controller to the robot. The controller is evaluated in a real-world flawed
unscrewing task with a Franka Emika Panda and is compared to a standard
impedance controller and a hybrid force-impedance controller. The results
demonstrate the high potential of the algorithm in human-robot collaborative
disassembly tasks.Comment: 7 pages, 6 figures, presented at the 2023 IEEE International
Conference on Robotics and Automation (ICRA). Video available at
https://www.youtube-nocookie.com/embed/SgYFHMlEl0
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