Chen Weidong - Intelligent autonomous systems 14: proceedings of the 14th International Conference IAS-14

Intelligent autonomous systems 14: proceedings of the 14th International Conference IAS-14 — read online for free the complete book (whole text) full work

Below is the text of the book, divided by pages. System saving the place of the last page read, allows you to conveniently read the book "Intelligent autonomous systems 14: proceedings of the 14th International Conference IAS-14" online for free, without having to search again every time where you left off. Put a bookmark, and you can go to the page where you finished reading at any time.

Light

Font size:

↓

↑

Georgia Tahoma Arial Verdana

Reset

Interval:

↓

↑

Bookmark:

Make

1234567...325

Part I
Embodied-Brain Systems Science

Springer International Publishing AG 2017

Weidong Chen , Koh Hosoda , Emanuele Menegatti , Masahiro Shimizu and Hesheng Wang (eds.) Intelligent Autonomous Systems 14 Advances in Intelligent Systems and Computing 10.1007/978-3-319-48036-7_1

Clustering Latent Sensor Distribution on Body Map for Generating Body Schema

Tomohiro Mimura 1

(1)

Ritsumeikan University, 1-1-1 Noji Higashi, Kusatsu Shiga, 525-8577, Japan

(2)

National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku Tokyo, 101-8430, Japan

Tomohiro Mimura (Corresponding author)

Email:

Yoshinobu Hagiwara (Corresponding author)

Email:

Tadahiro Taniguchi (Corresponding author)

Email:

Tetsunari Inamura (Corresponding author)

Email:

Abstract

A computational theory model is constructed to generate a body map and a body schema. It is assumed that the fetus has a body map and a body schema to control and understand its body and generates them based on tactile information obtained by random motion in the womb called general movement. As a first step, in this research, a computational theory model is proposed to generate the body Map based on tactile information and to estimate nodes of the body schema by machine learning methods.

Keywords

Body map Body schema Clustering

Introduction

Human beings can unconsciously control their bodies based on a musculoskeletal system that is constructed by integrating multimodal information in their brains [.

In previous research, Prechtl et al. reported that a fetus obtains a body schema through random motion in the womb called general movement []. General movement is defined as spontaneous activity by the fetus manifested as a smooth and random whole-body motion observed from 8.5 to 9.5 weeks. It is assumed that the fetus generates a body schema based on the relationship between motion and tactile information obtained by general movement because neighboring recipient-cells return similar tactile information owing to the high viscosity of amniotic fluid.

In this study, we aim to construct a computational model that generates a body map and a body schema based on tactile information obtained by random motion, i.e., general movement.

The computational model generates a body map by using multidimensional scaling (MDS) [] from the generated body map.

Fig. 1

A body map and a body schema in the human brain

Previous Research

2.1 Body Map

Human beings have body maps that are topological maps for their bodies in the brain []. Like an exhaustive patchwork body maps cover not only external body parts such as fingers, shoulders, elbows, and so on but also viscera.

In a previous study of body maps, Olsson et al. proposed a method to calculate an information measure based on the information of sensors attached to the robot AIBO and to replace each sensor with a two-dimensional map based on the calculated information measure []. However, this study is not intended for estimation of a multilink system.

Mori et al. provided a constructive model of a human fetus that forms behaviors and understanding regarding its body through general movements in the womb of its mother [].

2.2 Body Schema

Even though the human body has multiple degrees of freedom, human beings can control their bodies without considering the angle of joints and the length of links. It is assumed that a body schema enables human beings to unconsciously control their bodies. Humans have a multilink system in their brains for understanding their bodies. Henry et al. define body schema as a unconscious process that dynamically works when human beings control their motion and pose [].

In a previous study of body schema, Martinez et al. estimated a multilink system using an active-learning method based on vision information []. Nabeshima et al. proposed a model that enables robots to extend their body schema, when robots use tools, based on multimodal information. It is difficult to apply these methods to our study which to estimate body map and body schema based on tactile information because these methods require multimodal information including vision information.

Proposed Method

3.1 Overview

Figure a and b, respectively.

Fig. 2

Overview of the proposed approach. a Body map generation. b Node estimation. c Body schema generation

3.2 Generation of the Body Map

To generate a body map, we used the summation of conditional entropy and multidimensional scaling (MDS) []. The information metric d satisfies the following metric space axioms:

when the model has M tactile sensors, the information metric between two tactile sensors i and j is calculated from the equation:

(1)

where and are sets of tactile data at two sensors i and j , respectively. The conditional entropy is defined by the equation:

(2)

where x and y are tactile data and elements of and , respectively.

p ( y | x ) and p ( x ) have the following relationships from Bayes theorem:

(3)

(4)

Next page

1234567...325

Light

Font size:

↓

↑

Georgia Tahoma Arial Verdana

Reset

Interval:

↓

↑

Bookmark:

Make

Similar books «Intelligent autonomous systems 14: proceedings of the 14th International Conference IAS-14»

Look at similar books to Intelligent autonomous systems 14: proceedings of the 14th International Conference IAS-14. We have selected literature similar in name and meaning in the hope of providing readers with more options to find new, interesting, not yet read works.

Garima Mathur (editor)

Proceedings of 2nd International Conference on Artificial Intelligence: Advances and Applications: ICAIAA 2021 (Algorithms for Intelligent Systems)

Jie Chen

Distributed Artificial Intelligence: Third International Conference, DAI 2021, Shanghai, China, December 17–18, 2021, Proceedings

Nikhil Marriwala

Soft Computing for Intelligent Systems: Proceedings of ICSCIS 2020

Markus Vincze

Computer Vision Systems: 13th International Conference, ICVS 2021, Virtual Event, September 22-24, 2021, Proceedings

Charles Fox

Towards Autonomous Robotic Systems: 22nd Annual Conference, TAROS 2021, Lincoln, UK, September 8–10, 2021, Proceedings

Juan José Gude Prego

14th International Conference on Computational Intelligence in Security for Information Systems and 12th International Conference on European ... in Intelligent Systems and Computing)

Christian Hochberger (editor)

Architecture of Computing Systems: 34th International Conference, ARCS 2021, Virtual Event, June 7–8, 2021, Proceedings

Daniela Fogli

End-User Development: 8th International Symposium, IS-EUD 2021, Virtual Event, July 6–8, 2021, Proceedings

Robin R. Murphy

Introduction to AI Robotics (Intelligent Robotics and Autonomous Agents series)

Józef Korbicz (editor)

Advances in Diagnostics of Processes and Systems: Selected Papers from the 14th International Conference on Diagnostics of Processes and Systems ... in Systems, Decision and Control, 313)

Abraham Ajith.

Intelligent Systems Design and Applications: 16th International Conference on Intelligent Systems Design and Applications (ISDA 2016) held in Porto, Portugal, December 16-18, 2016

Ronald C. Arkin

Behavior-Based Robotics

Discussion, reviews of the book Intelligent autonomous systems 14: proceedings of the 14th International Conference IAS-14 and just readers' own opinions. Leave your comments, write what you think about the work, its meaning or the main characters. Specify what exactly you liked and what you didn't like, and why you think so.