Research on Human Cognition for Biologically Inspired Developments

2017 ◽  
pp. 83-116 ◽  
Author(s):  
Marko Wehle ◽  
Alexandra Weidemann ◽  
Ivo Wilhelm Boblan
Keyword(s):  
Role Model ◽  
Cognitive Model ◽  
Human Robot Interaction ◽  
Human Cognition ◽  
Biologically Inspired ◽  
Robot Interaction ◽  
Intelligent Machines ◽  
The World ◽  
Conducting Research ◽  
Interaction Research

Robotic developments are seen as a next level in technology with intelligent machines, which automate tedious tasks and serve our needs without complaints. But nevertheless, they have to be fair and smart enough to be intuitively of use and safe to handle. But how to implement this kind of intelligence, does it need feelings and emotions, should robots perceive the world as we do as a human role model, how far should the implementation of synthetic consciousness lead and actually, what is needed for consciousness in that context? Additionally in Human-Robot-Interaction research, science mainly makes use of the tool phenomenography, which is exclusively subjective, so how to make it qualify for Artificial Intelligence? These are the heading aspects of this chapter for conducting research in the field of social robotics and suggesting a conscious and cognitive model for smart and intuitive interacting robots, guided by biomimetics.

Research on Human Cognition for Biologically Inspired Developments

2020 ◽  
pp. 1507-1532
Author(s):  
Marko Wehle ◽  
Alexandra Weidemann ◽  
Ivo Wilhelm Boblan
Keyword(s):  
Role Model ◽  
Cognitive Model ◽  
Human Robot Interaction ◽  
Human Cognition ◽  
Biologically Inspired ◽  
Robot Interaction ◽  
Intelligent Machines ◽  
The World ◽  
Conducting Research ◽  
Interaction Research

Robotic developments are seen as a next level in technology with intelligent machines, which automate tedious tasks and serve our needs without complaints. But nevertheless, they have to be fair and smart enough to be intuitively of use and safe to handle. But how to implement this kind of intelligence, does it need feelings and emotions, should robots perceive the world as we do as a human role model, how far should the implementation of synthetic consciousness lead and actually, what is needed for consciousness in that context? Additionally in Human-Robot-Interaction research, science mainly makes use of the tool phenomenography, which is exclusively subjective, so how to make it qualify for Artificial Intelligence? These are the heading aspects of this chapter for conducting research in the field of social robotics and suggesting a conscious and cognitive model for smart and intuitive interacting robots, guided by biomimetics.

Humans and humanoids

2018 ◽  
Author(s):  
Giorgio Metta
Keyword(s):  
Humanoid Robot ◽  
Robot Vision ◽  
Physical Space ◽  
Humanoid Robots ◽  
Human Robot Interaction ◽  
Biologically Inspired ◽  
Robot Interaction ◽  
Humanoid Robotics ◽  
Biomimetic Robot ◽  
Compliant Actuation

This chapter outlines a number of research lines that, starting from the observation of nature, attempt to mimic human behavior in humanoid robots. Humanoid robotics is one of the most exciting proving grounds for the development of biologically inspired hardware and software—machines that try to recreate billions of years of evolution with some of the abilities and characteristics of living beings. Humanoids could be especially useful for their ability to “live” in human-populated environments, occupying the same physical space as people and using tools that have been designed for people. Natural human–robot interaction is also an important facet of humanoid research. Finally, learning and adapting from experience, the hallmark of human intelligence, may require some approximation to the human body in order to attain similar capacities to humans. This chapter focuses particularly on compliant actuation, soft robotics, biomimetic robot vision, robot touch, and brain-inspired motor control in the context of the iCub humanoid robot.

scholarly journals A Bio-inspired Motivational Decision Making System for Social Robots Based on the Perception of the User

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2691 ◽  
Author(s):  
Marcos Maroto-Gómez ◽  
Álvaro Castro-González ◽  
José Castillo ◽  
María Malfaz ◽  
Miguel Salichs
Keyword(s):  
Decision Making ◽  
Human Robot Interaction ◽  
Learning Mechanisms ◽  
Biologically Inspired ◽  
Robot Interaction ◽  
Detection Mechanism ◽  
Learned Behaviors ◽  
Decision Making System ◽  
Real Robot ◽  
Self Learning

Nowadays, many robotic applications require robots making their own decisions and adapting to different conditions and users. This work presents a biologically inspired decision making system, based on drives, motivations, wellbeing, and self-learning, that governs the behavior of the robot considering both internal and external circumstances. In this paper we state the biological foundations that drove the design of the system, as well as how it has been implemented in a real robot. Following a homeostatic approach, the ultimate goal of the robot is to keep its wellbeing as high as possible. In order to achieve this goal, our decision making system uses learning mechanisms to assess the best action to execute at any moment. Considering that the proposed system has been implemented in a real social robot, human-robot interaction is of paramount importance and the learned behaviors of the robot are oriented to foster the interactions with the user. The operation of the system is shown in a scenario where the robot Mini plays games with a user. In this context, we have included a robust user detection mechanism tailored for short distance interactions. After the learning phase, the robot has learned how to lead the user to interact with it in a natural way.

scholarly journals Human Cognition in Interaction With Robots: Taking the Robot’s Perspective Into Account

2020 ◽  
pp. 001872082093376
Author(s):  
Sophia von Salm-Hoogstraeten ◽  
Jochen Müsseler
Keyword(s):  
Production Process ◽  
Response Times ◽  
Error Rates ◽  
Human Robot Interaction ◽  
Human Cognition ◽  
Robot Interaction ◽  
Shared Workspace ◽  
Stimulus Response ◽  
Processing Times ◽  
Shared Workspaces

Objective The present study investigated whether and how different human–robot interactions in a physically shared workspace influenced human stimulus–response (SR) relationships. Background Human work is increasingly performed in interaction with advanced robots. Since human–robot interaction often takes place in physical proximity, it is crucial to investigate the effects of the robot on human cognition. Method In two experiments, we compared conditions in which humans interacted with a robot that they either remotely controlled or monitored under otherwise comparable conditions in the same shared workspace. The cognitive extent to which the participants took the robot’s perspective served as a dependent variable and was evaluated with a SR compatibility task. Results The results showed pronounced compatibility effects from the robot’s perspective when participants had to take the perspective of the robot during the task, but significantly reduced compatibility effects when human and robot did not interact. In both experiments, compatibility effects from the robot’s perspective resulted in statistically significant differences in response times and in error rates between compatible and incompatible conditions. Conclusion We concluded that SR relationships from the perspective of the robot need to be considered when designing shared workspaces that require users to take the perspective of the robot. Application The results indicate changed compatibility relationships when users share their workplace with an interacting robot and therefore have to take its perspective from time to time. The perspective-dependent processing times are expected to be accompanied by corresponding error rates, which might affect—for instance—safety and efficiency in a production process.

scholarly journals Long-term evaluation of a social robot in real homes

2016 ◽  
Vol 17 (3) ◽  
pp. 461-490 ◽  
Author(s):  
Maartje M. A. de Graaf ◽  
Somaya Ben Allouch ◽  
Jan A. G. M. van Dijk
Keyword(s):  
Social Presence ◽  
Mental Image ◽  
Human Robot Interaction ◽  
Control Beliefs ◽  
Mere Exposure Effect ◽  
Robot Interaction ◽  
Exposure Effect ◽  
Term Evaluation ◽  
Interaction Research

Abstract This study aims to contribute to emerging human-robot interaction research by adding longitudinal findings to a limited number of long-term social robotics home studies. We placed 70 robots in users’ homes for a period of up to six months, and used questionnaires and interviews to collect data at six points during this period. Results indicate that users’ evaluations of the robot dropped initially, but later rose after the robot had been used for a longer period of time. This is congruent with the so-called mere-exposure effect, which shows an increasing positive evaluation of a novel stimulus once people become familiar with it. Before adoption, users focus on control beliefs showing that previous experiences with robots or other technologies allows to create a mental image of what having and using a robot in the home would entail. After adoption, users focus on utilitarian and hedonic attitudes showing that especially usefulness, social presence, enjoyment and attractiveness are important factors for long-term acceptance.

scholarly journals KASPAR – a minimally expressive humanoid robot for human–robot interaction research

2009 ◽  
Vol 6 (3-4) ◽  
pp. 369-397 ◽  
Author(s):  
Kerstin Dautenhahn ◽  
Chrystopher L. Nehaniv ◽  
Michael L. Walters ◽  
Ben Robins ◽  
Hatice Kose-Bagci ◽  
...  
Keyword(s):  
Humanoid Robot ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Interaction Research

scholarly journals Human-Like Arm Motion Generation: A Review

2020 ◽  
Author(s):  
Gianpaolo Gulletta ◽  
Wolfram Erlhagen ◽  
Estela Bicho
Keyword(s):  
Human Robot Interaction ◽  
Motion Generation ◽  
Biologically Inspired ◽  
Robot Interaction ◽  
Arm Reaching ◽  
Strong Focus ◽  
Human Likeness ◽  
Human Motor ◽  
Arm Motion ◽  
Personal Robotics

In the last decade, the objectives outlined by the needs of personal robotics have led to the rise of new biologically-inspired techniques for arm motion planning. This paper presents a literature review of the most recent research on the generation of human-like arm movements in humanoid and manipulation robotic systems. Search methods and inclusion criteria are described. The studies are analysed taking into consideration the sources of publication, the experimental settings, the type of movements, the technical approach, and the human motor principles that have been used to inspire and assess human-likeness. Results show that there is a strong focus on the generation of single-arm reaching movements and biomimetic-based methods. However, there has been poor attention to manipulation, obstacle-avoidance mechanisms, and dual-arm motion generation. For these reasons, human-like arm motion generation may not fully respect human behavioural and neurological key features and may result restricted to specific tasks of human-robot interaction. Limitations and challenges are discussed to provide meaningful directions for future investigations.

scholarly journals Joint action with iCub: a successful adaptation of a paradigm of cognitive neuroscience in HRI

2019 ◽  
Author(s):  
Jairo Pérez-Osorio ◽  
Davide De Tommaso ◽  
Ebru Baykara ◽  
Agnieszka Wykowska
Keyword(s):  
Cognitive Psychology ◽  
Human Brain ◽  
Cognitive Neuroscience ◽  
Human Robot Interaction ◽  
Human Cognition ◽  
Social Environments ◽  
Social Signals ◽  
Robot Interaction ◽  
Robot Behavior ◽  
The Impact

Robots will soon enter social environments shared with humans. We need robots that are able to efficiently convey social signals during interactions. At the same time, we need to understand the impact of robots’ behavior on the human brain. For this purpose, human behavioral and neural responses to the robot behavior should be quantified offering feedback on how to improve and adjust robot behavior. Under this premise, our approach is to use methods of experimental psychology and cognitive neuroscience to assess the human’s reception of a robot in human-robot interaction protocols. As an example of this approach, we report an adaptation of a classical paradigm of experimental cognitive psychology to a naturalistic human- robot interaction scenario. We show the feasibility of such an approach with a validation pilot study, which demonstrated that our design yielded a similar pattern of data to what has been previously observed in experiments within the area of cognitive psychology. Our approach allows for addressing specific mechanisms of human cognition that are elicited during human-robot interaction, and thereby, in a longer-term perspective, it will allow for designing robots that are well- attuned to the workings of the human brain.

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