Author
Masaki Ogino
Other affiliations: Osaka University
Bio: Masaki Ogino is an academic researcher from Kansai University. The author has contributed to research in topics: Humanoid robot & Representation (systemics). The author has an hindex of 15, co-authored 60 publications receiving 1039 citations. Previous affiliations of Masaki Ogino include Osaka University.
Papers published on a yearly basis
Papers
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TL;DR: Cognitive developmental robotics aims to provide new understanding of how human's higher cognitive functions develop by means of a synthetic approach that developmentally constructs cognitive functions through interactions with the environment, including other agents.
Abstract: Cognitive developmental robotics (CDR) aims to provide new understanding of how human's higher cognitive functions develop by means of a synthetic approach that developmentally constructs cognitive functions. The core idea of CDR is ldquophysical embodimentrdquo that enables information structuring through interactions with the environment, including other agents. The idea is shaped based on the hypothesized development model of human cognitive functions from body representation to social behavior. Along with the model, studies of CDR and related works are introduced, and discussion on the model and future issues are argued.
519 citations
TL;DR: A learning model is proposed that enables a robot to acquire a body image for parts of its body that are invisible to itself and associates spatial perception based on motor experience.
Abstract: This paper proposes a learning model that enables a robot to acquire a body image for parts of its body that are invisible to itself. The model associates spatial perception based on motor experien...
49 citations
01 Jan 2006
TL;DR: The ongoing development of the 3D simulator which is being extended to simulate a real humanoid robot and an insight into the current behavior development framework of the Humanoid League team Senchans is given.
Abstract: This paper presents the current efforts and ideas of members in the RoboCup Simulation and the Humanoid Leagues to take successful concepts from both environments and extend them in ways so that each league can profit from the results. We describe the ongoing development of the 3D simulator which is being extended to simulate a real humanoid robot. At the same time, we give an insight into the current behavior development framework of the Humanoid League team Senchans which makes heavy use of techniques which have been successfully used in the Simulation League before. Furthermore, we give some suggestions for a collaboration between the different leagues in the RoboCup from which all the participants could benefit.
48 citations
TL;DR: This work model human intuitive parenting using a robot that associates a caregiver's mimicked or exaggerated facial expressions with the robot’s internal state to learn a sympathetic response.
Abstract: Sympathy is a key issue in interaction and communication between robots and their users. In developmental psychology, intuitive parenting is considered the maternal scaffolding upon which children develop sympathy when caregivers mimick or exaggerate the child’s emotional facial expressions [1]. We model human intuitive parenting using a robot that associates a caregiver’s mimicked or exaggerated facial expressions with the robot’s internal state to learn a sympathetic response. The internal state space and facial expressions are defined using psychological studies and change dynamically in response to external stimuli. After learning, the robot responds to the caregiver’s internal state by observing human facial expressions. The robot then expresses its own internal state facially if synchronization evokes a response to the caregiver’s internal state.
45 citations
TL;DR: This paper proposes a system for a humanoid who obtains new motions through learning the interaction rules with a human partner based on the assumption of the mirror system, and learns an interaction rule that control gesture turn-taking.
38 citations
Cited by
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TL;DR: A comprehensive survey of robot Learning from Demonstration (LfD), a technique that develops policies from example state to action mappings, which analyzes and categorizes the multiple ways in which examples are gathered, as well as the various techniques for policy derivation.
3,343 citations
01 Jan 2010
TL;DR: In this paper, the authors describe a scenario where a group of people are attempting to find a solution to the problem of "finding the needle in a haystack" in the environment.
Abstract: 中枢神経系疾患の治療は正常細胞（ニューロン）の機能維持を目的とするが，脳血管障害のように機能障害の原因が細胞の死滅に基づくことは多い．一方，脳腫瘍の治療においては薬物療法や放射線療法といった腫瘍細胞の死滅を目標とするものが大きな位置を占める．いずれの場合にも，細胞死の機序を理解することは各種病態や治療法の理解のうえで重要である．現在のところ最も研究の進んでいる細胞死の型はアポトーシスである．そのなかで重要な位置を占めるミトコンドリアにおける反応および抗アポトーシス因子について概要を紹介する．
2,716 citations
TL;DR: In this article, a review of recent progress in cognitive science suggests that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn and how they learn it.
Abstract: Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should (1) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (2) ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and (3) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models.
2,010 citations
TL;DR: Research carried out on locomotor central pattern generators (CPGs), i.e. neural circuits capable of producing coordinated patterns of high-dimensional rhythmic output signals while receiving only simple, low-dimensional, input signals, is reviewed.
1,737 citations
Book•
24 Aug 2009
TL;DR: Programming by demonstration (PbD) as discussed by the authors is a technique for teaching new skills to a robot by imitation, tutelage, or apprenticeship learning through human guidance.
Abstract: Also referred to as learning by imitation, tutelage, or apprenticeship learning, Programming by Demonstration (PbD) develops methods by which new skills can be transmitted to a robot. This book examines methods by which robots learn new skills through human guidance. Taking a practical perspective, it covers a broad range of applications, including service robots. The text addresses the challenges involved in investigating methods by which PbD is used to provide robots with a generic and adaptive model of control. Drawing on findings from robot control, human-robot interaction, applied machine learning, artificial intelligence, and developmental and cognitive psychology, the book contains a large set of didactic and illustrative examples. Practical and comprehensive machine learning source codes are available on the books companion website: http://www.programming-by-demonstration.org
1,071 citations