Header

UZH-Logo

Maintenance Infos

Local information transfer in soft robotic arm


Nakajima, Kohei; Li, Tao; Kang, Rongjie; Guglielmino, Emanuele; Caldwell, Darwin G; Pfeifer, Rolf (2012). Local information transfer in soft robotic arm. In: IEEE International Conference on Robotics and Biomimetics (ROBIO 2012), Guangzhou, China, 11 December 2012 - 14 December 2012, 1273-1280.

Abstract

Recently, the information theoretic approach has been increasingly used in the robotics community as powerful quantitative measures for characterizing the dynamic coupling between the controller, the body, and the environment in embodied robots. This approach is effective and useful even if this interaction regime becomes complex and nonlinear as is often the case in soft robots. In this study, we propose a method for characterizing and visualizing the information transfer spatiotemporally through the robot’s body. This method is based on the framework called “local information transfer” proposed by Lizier et al. We extend it with the permutation-information theoretic approach, which makes it feasible for continuous time series data usually obtained in robotic platforms. To test the power of the proposed method, we performed experiments using a soft robotic arm simulator and a silicone-based soft robotic arm platform inspired by the octopus and showed that the external damage spreading is successfully and clearly visualized by the method. We also analyzed the robustness of the method to noise. Finally, we discuss future applications and possible extensions.

Abstract

Recently, the information theoretic approach has been increasingly used in the robotics community as powerful quantitative measures for characterizing the dynamic coupling between the controller, the body, and the environment in embodied robots. This approach is effective and useful even if this interaction regime becomes complex and nonlinear as is often the case in soft robots. In this study, we propose a method for characterizing and visualizing the information transfer spatiotemporally through the robot’s body. This method is based on the framework called “local information transfer” proposed by Lizier et al. We extend it with the permutation-information theoretic approach, which makes it feasible for continuous time series data usually obtained in robotic platforms. To test the power of the proposed method, we performed experiments using a soft robotic arm simulator and a silicone-based soft robotic arm platform inspired by the octopus and showed that the external damage spreading is successfully and clearly visualized by the method. We also analyzed the robustness of the method to noise. Finally, we discuss future applications and possible extensions.

Statistics

Citations

Altmetrics

Downloads

2 downloads since deposited on 01 Feb 2013
0 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:14 December 2012
Deposited On:01 Feb 2013 07:56
Last Modified:03 Aug 2017 00:02
Publisher:IEEE
ISBN:978-1-4673-2126-6
Related URLs:http://www.ualberta.ca/~robio12/
Other Identification Number:merlin-id:7853

Download

Preview Icon on Download
Content: Published Version
Filetype: PDF - Registered users only
Size: 8MB