Morphological optimization for tensegrity quadruped locomotion

The increasing complexity of soft and hybrid-soft robots highlights the need for more efficient methods of minimizing machine learning solution spaces, and creative ways to ease the process of rapid prototyping. In this paper, we present an initial exploration of this process, using hand-chosen morp...

Full description

Saved in:
Bibliographic Details
Published in2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) pp. 3990 - 3995
Main Authors Hustig-Schultz, Dawn, SunSpiral, Vytas, Teodorescu, Mircea
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2017
Subjects
Actuators
Impedance
Legged locomotion
Morphology
Muscles
Tendons
Online AccessGet full text

Cover

More Information
Summary:The increasing complexity of soft and hybrid-soft robots highlights the need for more efficient methods of minimizing machine learning solution spaces, and creative ways to ease the process of rapid prototyping. In this paper, we present an initial exploration of this process, using hand-chosen morphologies. Four different choices of muscle groups will be actuated on a tensegrity quadruped called MountainGoat: three for a primarily spine-driven morphology, and one for a primarily leg-driven morphology, and the locomotion speed will be compared. Each iteration of design seeks to reduce the total number of active muscles, and consequently reduce the dimensionality of the problem for machine learning, while still producing effective locomotion. The reduction in active muscles seeks to simplify future rapid prototyping of the robot.
ISSN:2153-0866
DOI:10.1109/IROS.2017.8206253