changeset 12:e5967e62ebde

Mini fixes
author Yasutaka Higa <>
date Fri, 26 Jun 2015 10:01:23 +0900
parents 7104d522d2f0
children eb59659c9c02
diffstat 1 files changed, 3 insertions(+), 13 deletions(-) [+]
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line diff
--- a/	Fri Jun 26 09:38:20 2015 +0900
+++ b/	Fri Jun 26 10:01:23 2015 +0900
@@ -23,13 +23,6 @@
 * As the importance of culture-specific customization of greeting was confirmed.
 * Acceptance of robots can be improved if they are able to adapt to different kinds of greeting rules.
-# Introduction: Methods of implementation adaptive behaviour
-* Adaptive behaviour in robotics can be achieved through various methods:
-    * reinforcement learning
-    * neural networks
-    * generic algorithms
-    * function regression
 # Introduction: Greeting interaction with robots
 * Robots are expected to interact and communicate with humans of different cultural background in a natural way.
 * It is there therefore important to study greeting interaction between robots and humans.
@@ -39,7 +32,6 @@
 # Introduction: Objectives of this paper
 * The robot should be trained with sociology data related to one country, and evolve its behaviour by engaging with people of another country in a small number of interactions.
-* For the implementation of the gestures and the interaction experiment, we used the humanoid robot ARMAR-IIIb.
 * As the experiment is carried out in Germany, the interactions are with German participants, while preliminary training is done with Japanese data, which is culturally extremely different.
 # Introduction: ARMAR-IIIb
@@ -159,8 +151,6 @@
 * Thanks to this implementation, mappings can evolve quickly, without requiring hundreds or thousands of iterations
 * but rather a number comparable to the low number of interactions humans need to understand and adapt to social rules.
-# TODO: Please Add slides over chapter (3. implementation of ARMAR-IIIb)
 # Implementation on ARMAR-IIIb
 * ARMAR-III is designed for close cooperation with humans
 * ARMAR-III has a humanlike appearance
@@ -182,7 +172,7 @@
 <img src="pictures/MMM.png" style='width: 60%; margin-left: 150px; margin-top: -50px;'>
 # Master Motor Map
-* The body model of MMM  model can be seen in the left-hand illustration in Figure 
+* The body model of MMM  model can be seen in the left-hand illustration in Figure
 * It contains some joints, such as the clavicula, which are usually not implemented in humanoid robots
 * A conversion module is necessary to perform a transformation between this kinematic model and ARMAR-IIIb kinematic model
@@ -190,7 +180,7 @@
 <img src="pictures/MMMModel.png" style='width: 60%; margin-left: 150px; margin-top: -50px;'>
-# MMM support 
+# MMM support
 * The MMM framework has a high support for every kind of human-like robot
 * MMM can define the transfer rules
 * Using the conversion rules, it can be converted from the MMM Model to the movement of the robot
@@ -284,7 +274,7 @@
 # Results
 * It referred to how the change in the gesture of the experiment
 * It has become common Bowing is greatly reduced handshake
-* It has appeared hug that does not exist in Japan of mapping 
+* It has appeared hug that does not exist in Japan of mapping
 * This is because the participants issued a feedback that hug is appropriate
 # Results