Open AccessCombining Locomotion and Grasping Functionalities in Soft Robots
Author(s) -
Yin Alexander,
Lin Hung-Ching,
Thelen Joanna,
Mahner Benjamin,
Ranzani Tommaso
Publication year - 2019
Publication title -
advanced intelligent systems
Language(s) - English
Resource type - Journals
ISSN - 2640-4567
DOI - 10.1002/aisy.201900089
Subject(s) - payload (computing) , robot , soft robotics , robotics , artificial intelligence , computer science , soft materials , robot locomotion , degrees of freedom (physics and chemistry) , control engineering , simulation , engineering , mobile robot , robot control , physics , nanotechnology , computer network , materials science , quantum mechanics , network packet
In recent years, the field of soft robotics has grown considerably, demonstrating robots with advanced locomotion capabilities as well as robust grasping and manipulation with respect to their rigid counterparts. The combination of locomotion and grasping capabilities entails a unique set of challenges in soft robotics that have not been fully explored yet, such as the capability to carry a payload without compromising its motion capabilities, and how to adjust changes in the center of mass of the robot. Herein, a soft robotic platform is proposed that demonstrates simultaneous locomotion and grasping. The challenges that such a soft robot would encounter are explored in terms of stability of the robot while supporting a payload and variations in the location of the center of mass. The robot has 13 independently controllable degrees of freedom to study different locomotion and grasping strategies. A passive stiffening methodology is also presented that allows the robot body to statically sustain up to 7.7 times its body weight (BW), and to walk carrying a payload up to 100% times its BW.