This project seeks to extend our understanding of the principles underlying the design and control of effective soft robots. Soft robots and muscle-like soft actuators coupled with agile control strategies will enable new manipulation and locomotion capabilities currently only found in nature, and allow robots and humans to safely collaborate. Today's industrial manipulators enable rapid and precise assembly, but these robots are physically isolated, to ensure the safety of any humans nearby. In contrast, the bodies of soft robots are made of intrinsically soft and/or extensible materials, such as silicone rubbers or fabrics, and are therefore safe for interaction with humans and animals. Soft robots have a continuously deformable structure with muscle-like actuation that emulates key features of biological systems and provides them with a relatively large number of degrees of freedom as compared to their hard-bodied counterparts. Soft robots have capabilities beyond what is possible with today's rigid-bodied robots. For example, soft-bodied robots can move in more natural ways that include complex bending and twisting curvatures that are not restricted to the traditional rigid body kinematics of existing robotic manipulators. Their bodies can deform in a continuous way, providing theoretically infinite degrees of freedom and allowing them to adapt their shape to their task, for example, conforming to natural terrain or forming enveloping grasps. Soft robots have also been shown to be capable of rapid agile maneuvers and can change their stiffness to achieve a task- or environment-specific impedance. Current research on device-level and algorithmic aspects of soft robots has resulted in a range of novel soft devices. This project will derive a systematic mathematical framework to model and control soft robots and will use the resulting algorithms to perform manipulation tasks with a wide variety of delicacy and strength requirements. The results will have potential uses in manufacturing, warehouse and supply chain automation, and everyday home activities such as cooking and cleaning. These soft, strong, and safe robots will have potential application in assisted care for the elderly or disabled, and for physical therapy. This project uses the unique features of soft robots to continue the Principal Investigators' track record of outreach and educational activities that excite young students about STEM careers.

In the recent past, the soft robotics community has explored many different component hardware technologies, however fundamental algorithmic obstacles to their practical use remain challenging. Currently there is an artificial divide between control strategies for rigid and soft robots; rigid robots use high-bandwidth control of contact forces and contact geometry, while soft robots rely almost entirely on open-loop interactions, mediated by material properties, to govern the resulting forces and configurations. This project will bridge this gap by developing optimization-based control for soft robots, via approximate dynamic models of the soft interface, based on representations with a fidelity customized to the task. The proposed class of soft, strong, and safe robots will be designed, fabricated, and controlled by co-developing muscle-like actuation along with internal and contact models and associated planning and control strategies. An innovative new artificial muscle design allows customization of actuators to specific tasks, through systematic modular design. The modeling effort will focus on contact-rich behaviors of the soft robot with the environment, both for delicate touch and manipulation, and for high-force power grasps. Such a combination of soft and strong has not been fully addressed in the soft robotics community and will allow soft robots to interact safely and effectively with people in unprecedented applications.

This project is jointly sponsored by the National Science Foundation, Office of Emerging Frontiers and Multidisciplinary Activities (EFMA) and the US Air Force Office of Scientific Research (AFOSR).

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Emerging Frontiers (EF)
Type
Standard Grant (Standard)
Application #
1830901
Program Officer
Jordan Berg
Project Start
Project End
Budget Start
2018-09-01
Budget End
2022-08-31
Support Year
Fiscal Year
2018
Total Cost
$2,000,000
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Type
DUNS #
City
Cambridge
State
MA
Country
United States
Zip Code
02139