Dynamics and trajectory optimization for a soft spatial fluidic elastomer manipulator

• Main Authors: Marchese, Andrew Dominic (Contributor), Tedrake, Russell Louis (Contributor), Rus, Daniela L. (Contributor)
• Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE), 2016-01-29T02:17:47Z.
• Subjects: Article
• Online Access: Get fulltext

The goal of this work is to develop a soft robotic manipulation system that is capable of autonomous, dynamic, and safe interactions with humans and its environment. First, we develop a dynamic model for a multi-body fluidic elastomer manipulator that is composed entirely from soft rubber and subject to the self-loading effects of gravity. Then, we present a strategy for independently identifying all unknown components of the system: the soft manipulator, its distributed fluidic elastomer actuators, as well as drive cylinders that supply fluid energy. Next, using this model and trajectory optimization techniques we find locally optimal open-loop policies that allow the system to perform dynamic maneuvers we call grabs. In 37 experimental trials with a physical prototype, we successfully perform a grab 92% of the time. By studying such an extreme example of a soft robot, we can begin to solve hard problems inhibiting the mainstream use of soft machines.
National Science Foundation (U.S.) (Grant 1117178)
National Science Foundation (U.S.) (Grant EAGER 1133224)
National Science Foundation (U.S.) (Grant IIS1226883)
National Science Foundation (U.S.) (Grant CCF1138967)
National Science Foundation (U.S.). Graduate Research Fellowship (Award 1122374)