444 research outputs found
Conjunctive Visual and Auditory Development via Real-Time Dialogue
Human developmental learning is capable of
dealing with the dynamic visual world, speech-based
dialogue, and their complex real-time association.
However, the architecture that realizes
this for robotic cognitive development has
not been reported in the past. This paper takes
up this challenge. The proposed architecture does
not require a strict coupling between visual and
auditory stimuli. Two major operations contribute
to the โabstractionโ process: multiscale temporal
priming and high-dimensional numeric abstraction
through internal responses with reduced variance.
As a basic principle of developmental learning,
the programmer does not know the nature
of the world events at the time of programming
and, thus, hand-designed task-specific representation
is not possible. We successfully tested the
architecture on the SAIL robot under an unprecedented
challenging multimodal interaction mode:
use real-time speech dialogue as a teaching source
for simultaneous and incremental visual learning
and language acquisition, while the robot is viewing
a dynamic world that contains a rotating object
to which the dialogue is referring
Symbol Emergence in Robotics: A Survey
Humans can learn the use of language through physical interaction with their
environment and semiotic communication with other people. It is very important
to obtain a computational understanding of how humans can form a symbol system
and obtain semiotic skills through their autonomous mental development.
Recently, many studies have been conducted on the construction of robotic
systems and machine-learning methods that can learn the use of language through
embodied multimodal interaction with their environment and other systems.
Understanding human social interactions and developing a robot that can
smoothly communicate with human users in the long term, requires an
understanding of the dynamics of symbol systems and is crucially important. The
embodied cognition and social interaction of participants gradually change a
symbol system in a constructive manner. In this paper, we introduce a field of
research called symbol emergence in robotics (SER). SER is a constructive
approach towards an emergent symbol system. The emergent symbol system is
socially self-organized through both semiotic communications and physical
interactions with autonomous cognitive developmental agents, i.e., humans and
developmental robots. Specifically, we describe some state-of-art research
topics concerning SER, e.g., multimodal categorization, word discovery, and a
double articulation analysis, that enable a robot to obtain words and their
embodied meanings from raw sensory--motor information, including visual
information, haptic information, auditory information, and acoustic speech
signals, in a totally unsupervised manner. Finally, we suggest future
directions of research in SER.Comment: submitted to Advanced Robotic
A Review of Verbal and Non-Verbal Human-Robot Interactive Communication
In this paper, an overview of human-robot interactive communication is
presented, covering verbal as well as non-verbal aspects of human-robot
interaction. Following a historical introduction, and motivation towards fluid
human-robot communication, ten desiderata are proposed, which provide an
organizational axis both of recent as well as of future research on human-robot
communication. Then, the ten desiderata are examined in detail, culminating to
a unifying discussion, and a forward-looking conclusion
Sensorimotor Representation Learning for an โActive Selfโ in Robots: A Model Survey
Safe human-robot interactions require robots to be able to learn how to behave appropriately in spaces populated by people and thus to cope with the challenges posed by our dynamic and unstructured environment, rather than being provided a rigid set of rules for operations. In humans, these capabilities are thought to be related to our ability to perceive our body in space, sensing the location of our limbs during movement, being aware of other objects and agents, and controlling our body parts to interact with them intentionally. Toward the next generation of robots with bio-inspired capacities, in this paper, we first review the developmental processes of underlying mechanisms of these abilities: The sensory representations of body schema, peripersonal space, and the active self in humans. Second, we provide a survey of robotics models of these sensory representations and robotics models of the self; and we compare these models with the human counterparts. Finally, we analyze what is missing from these robotics models and propose a theoretical computational framework, which aims to allow the emergence of the sense of self in artificial agents by developing sensory representations through self-exploration.Deutsche Forschungsgemeinschaft
http://dx.doi.org/10.13039/501100001659Deutsche Forschungsgemeinschaft
http://dx.doi.org/10.13039/501100001659Deutsche Forschungsgemeinschaft
http://dx.doi.org/10.13039/501100001659Deutsche Forschungsgemeinschaft
http://dx.doi.org/10.13039/501100001659Deutsche Forschungsgemeinschaft
http://dx.doi.org/10.13039/501100001659Deutsche Forschungsgemeinschaft
http://dx.doi.org/10.13039/501100001659Projekt DEALPeer Reviewe
Sensorimotor representation learning for an "active self" in robots: A model survey
Safe human-robot interactions require robots to be able to learn how to
behave appropriately in \sout{humans' world} \rev{spaces populated by people}
and thus to cope with the challenges posed by our dynamic and unstructured
environment, rather than being provided a rigid set of rules for operations. In
humans, these capabilities are thought to be related to our ability to perceive
our body in space, sensing the location of our limbs during movement, being
aware of other objects and agents, and controlling our body parts to interact
with them intentionally. Toward the next generation of robots with bio-inspired
capacities, in this paper, we first review the developmental processes of
underlying mechanisms of these abilities: The sensory representations of body
schema, peripersonal space, and the active self in humans. Second, we provide a
survey of robotics models of these sensory representations and robotics models
of the self; and we compare these models with the human counterparts. Finally,
we analyse what is missing from these robotics models and propose a theoretical
computational framework, which aims to allow the emergence of the sense of self
in artificial agents by developing sensory representations through
self-exploration
๋ก๋ด์ ๊ณ ๊ฐ๋ฅผ ์์ง์ด๋ ๋์๊ณผ ํ์ด๋ฐ์ด ์ธ๊ฐ๊ณผ ๋ก๋ด์ ์ํธ์์ฉ์ ๋ฏธ์น๋ ํจ๊ณผ
ํ์๋
ผ๋ฌธ(์์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ์ธ๋ฌธ๋ํ ํ๋๊ณผ์ ์ธ์ง๊ณผํ์ ๊ณต, 2023. 2. Sowon Hahn.In recent years, robots with artificial intelligence capabilities have become ubiquitous in our daily lives. As intelligent robots are interacting closely with humans, social abilities of robots are increasingly more important. In particular, nonverbal communication can enhance the efficient social interaction between human users and robots, but there are limitations of behavior expression. In this study, we investigated how minimal head movements of the robot influence human-robot interaction. We newly designed a robot which has a simple shaped body and minimal head movement mechanism. We conducted an experiment to examine participants' perception of robots different head movements and timing. Participants were randomly assigned to one of three movement conditions, head nodding (A), head shaking (B) and head tilting (C). Each movement condition included two timing variables, prior head movement of utterance and simultaneous head movement with utterance. For all head movement conditions, participants' perception of anthropomorphism, animacy, likeability and intelligence were higher compared to non-movement (utterance only) condition. In terms of timing, when the robot performed head movement prior to utterance, perceived naturalness was rated higher than simultaneous head movement with utterance. The findings demonstrated that head movements of the robot positively affects user perception of the robot, and head movement prior to utterance can make human-robot conversation more natural. By implementation of head movement and movement timing, simple shaped robots can have better social interaction with humans.์ต๊ทผ ์ธ๊ณต์ง๋ฅ ๋ก๋ด์ ์ผ์์์ ํํ๊ฒ ์ ํ ์ ์๋ ๊ฒ์ด ๋์๋ค. ์ธ๊ฐ๊ณผ์ ๊ต๋ฅ๊ฐ ๋์ด๋จ์ ๋ฐ๋ผ ๋ก๋ด์ ์ฌํ์ ๋ฅ๋ ฅ์ ๋ ์ค์ํด์ง๊ณ ์๋ค. ์ธ๊ฐ๊ณผ ๋ก๋ด์ ์ฌํ์ ์ํธ์์ฉ์ ๋น์ธ์ด์ ์ปค๋ฎค๋์ผ์ด์
์ ํตํด ๊ฐํ๋ ์ ์๋ค. ๊ทธ๋ฌ๋ ๋ก๋ด์ ๋น์ธ์ด์ ์ ์ค์ฒ์ ํํ์ ์ ์ฝ์ ๊ฐ๋๋ค. ๋ํ ๋ก๋ด์ ์๋ต ์ง์ฐ ๋ฌธ์ ๋ ์ธ๊ฐ์ด ๋ถํธํ ์นจ๋ฌต์ ์๊ฐ์ ๊ฒฝํํ๊ฒ ํ๋ค. ๋ณธ ์ฐ๊ตฌ๋ฅผ ํตํด ๋ก๋ด์ ๊ณ ๊ฐ ์์ง์์ด ์ธ๊ฐ๊ณผ ๋ก๋ด์ ์ํธ์์ฉ์ ์ด๋ค ์ํฅ์ ๋ฏธ์น๋์ง ์์๋ณด์๋ค. ๋ก๋ด์ ๊ณ ๊ฐ ์์ง์์ ํ๊ตฌํ๊ธฐ ์ํด ๋จ์ํ ํ์๊ณผ ๊ณ ๊ฐ๋ฅผ ์์ง์ด๋ ๊ตฌ์กฐ๋ฅผ ๊ฐ์ง ๋ก๋ด์ ์๋กญ๊ฒ ๋์์ธํ์๋ค. ์ด ๋ก๋ด์ ํ์ฉํ์ฌ ๋ก๋ด์ ๋จธ๋ฆฌ ์์ง์๊ณผ ํ์ด๋ฐ์ด ์ฐธ์ฌ์์๊ฒ ์ด๋ป๊ฒ ์ง๊ฐ๋๋์ง ์คํํ์๋ค. ์ฐธ์ฌ์๋ค์ 3๊ฐ์ง ์์ง์ ์กฐ๊ฑด์ธ, ๋๋์ (A), ์ข์ฐ๋ก ์ ์ (B), ๊ธฐ์ธ์ (C) ์ค ํ ๊ฐ์ง ์กฐ๊ฑด์ ๋ฌด์์๋ก ์ ์ ๋์๋ค. ๊ฐ๊ฐ์ ๊ณ ๊ฐ ์์ง์ ์กฐ๊ฑด์ ๋ ๊ฐ์ง ํ์ด๋ฐ(์์ฑ๋ณด๋ค ์์ ๊ณ ๊ฐ ์์ง์, ์์ฑ๊ณผ ๋์์ ์ผ์ด๋๋ ๊ณ ๊ฐ ์์ง์)์ ๋ณ์๋ฅผ ๊ฐ๋๋ค. ๋ชจ๋ ํ์
์ ๊ณ ๊ฐ ์์ง์์์ ์์ง์์ด ์๋ ์กฐ๊ฑด๊ณผ ๋น๊ตํ์ฌ ๋ก๋ด์ ์ธ๊ฒฉํ, ํ๋์ฑ, ํธ๊ฐ๋, ๊ฐ์ง๋ ์ง๋ฅ์ด ํฅ์๋ ๊ฒ์ ๊ด์ฐฐํ์๋ค. ํ์ด๋ฐ์ ๋ก๋ด์ ์์ฑ๋ณด๋ค ๊ณ ๊ฐ ์์ง์์ด ์์ค ๋ ์์ฐ์ค๋ฌ์์ด ๋๊ฒ ์ง๊ฐ๋๋ ๊ฒ์ผ๋ก ๊ด์ฐฐ๋์๋ค. ๊ฒฐ๊ณผ์ ์ผ๋ก, ๋ก๋ด์ ๊ณ ๊ฐ ์์ง์์ ์ฌ์ฉ์์ ์ง๊ฐ์ ๊ธ์ ์ ์ธ ์ํฅ์ ์ฃผ๋ฉฐ, ์์ ํ์ด๋ฐ์ ๊ณ ๊ฐ ์์ง์์ด ์์ฐ์ค๋ฌ์์ ํฅ์์ํค๋ ๊ฒ์ ํ์ธํ์๋ค. ๊ณ ๊ฐ๋ฅผ ์์ง์ด๋ ๋์๊ณผ ํ์ด๋ฐ์ ํตํด ๋จ์ํ ํ์์ ๋ก๋ด๊ณผ ์ธ๊ฐ์ ์ํธ์์ฉ์ด ํฅ์๋ ์ ์์์ ๋ณธ ์ฐ๊ตฌ๋ฅผ ํตํด ํ์ธํ์๋ค.Chapter 1. Introduction 1
1.1. Motivation 1
1.2. Literature Review and Hypotheses 3
1.3. Purpose of Study 11
Chapter 2. Experiment 13
2.1. Methods 13
2.2. Results 22
2.3. Discussion 33
Chapter 3. Conclusion 35
Chapter 4. General Discussion 37
4.1. Theoretical Implications 37
4.2. Practical Implications 38
4.3. Limitations and Future work 39
References 41
Appendix 53
Abstract in Korean 55์
The Future of Humanoid Robots
This book provides state of the art scientific and engineering research findings and developments in the field of humanoid robotics and its applications. It is expected that humanoids will change the way we interact with machines, and will have the ability to blend perfectly into an environment already designed for humans. The book contains chapters that aim to discover the future abilities of humanoid robots by presenting a variety of integrated research in various scientific and engineering fields, such as locomotion, perception, adaptive behavior, human-robot interaction, neuroscience and machine learning. The book is designed to be accessible and practical, with an emphasis on useful information to those working in the fields of robotics, cognitive science, artificial intelligence, computational methods and other fields of science directly or indirectly related to the development and usage of future humanoid robots. The editor of the book has extensive R&D experience, patents, and publications in the area of humanoid robotics, and his experience is reflected in editing the content of the book
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Attentional mechanisms for socially interactive robots โ a survey
This review intends to provide an overview of the state of the art in the modeling and implementation of automatic attentional mechanisms for socially interactive robots. Humans assess and exhibit intentionality by resorting to multisensory processes that are deeply rooted within low-level automatic attention-related mechanisms of the brain. For robots to engage with humans properly, they should also be equipped with similar capabilities. Joint attention, the precursor of many fundamental types of social interactions, has been an important focus of research in the past decade and a half, therefore providing the perfect backdrop for assessing the current status of state-of-the-art automatic attentional-based solutions. Consequently, we propose to review the influence of these mechanisms in the context of social interaction in cutting-edge research work on joint attention. This will be achieved by summarizing the contributions already made in these matters in robotic cognitive systems research, by identifying the main scientific issues to be addressed by these contributions and analyzing how successful they have been in this respect, and by consequently drawing conclusions that may suggest a roadmap for future successful research efforts
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