| NSF Org: |
EFMA Office of Emerging Frontiers in Research and Innovation (EFRI) |
| Recipient: |
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| Initial Amendment Date: | August 16, 2018 |
| Latest Amendment Date: | August 16, 2018 |
| Award Number: | 1830901 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Jordan Berg
jberg@nsf.gov (703)292-5365 EFMA Office of Emerging Frontiers in Research and Innovation (EFRI) ENG Directorate for Engineering |
| Start Date: | September 1, 2018 |
| End Date: | August 31, 2024 (Estimated) |
| Total Intended Award Amount: | $2,000,000.00 |
| Total Awarded Amount to Date: | $2,000,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
77 MASSACHUSETTS AVE CAMBRIDGE MA US 02139-4301 (617)253-1000 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
MA US 02139-4307 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | EFRI Research Projects |
| Primary Program Source: |
01001819RB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
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.
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This research advances the design, sensing, and control of soft and hybrid robotic systems, with the ultimate aim of creating robots that are both soft and strong, capable of performing complex tasks safely around humans while interacting with dynamic and unstructured environments. Key contributions include innovations in hardware design, sensing integration, and control algorithms, spanning several specific outcomes.
Hardware Innovations:
On the hardware side, we developed multiple robotic hands and manipulators combining soft and rigid elements. Notable achievements include innovative grippers for grasping by entanglement, a “tulip”-shaped gripper that can lift 100x its weight due to an innovative enclosed origami skeleton, a multi-material 3D printed robot hand, and a 15-degree-of-freedom (DoF) pneumatically actuated hand, which integrates rigid joints and soft skin in a design that can be 3D printed with minimal assembly, drastically reducing production costs. This 15 DoF hand demonstrates proficiency in a range of tasks, including vision-based learning by teleoperation. Building on this work, the research also contributed a new cable-driven robotic hand that combines rigid and soft materials, with additional degrees of freedom in the palm to enhance dexterity. The hand is capable of tracking human hand motion in real time and executing various human-like grasping and manipulation tasks.
Sensing Integration:
We integrated innovative sensing mechanisms to enhance robotic capabilities. For example, fluidic innervation sensors embedded in soft robotic grippers were used to assess the weight and distribution of objects during grasping. This approach simplifies fabrication while providing robust, pressure-based internal sensing. The grippers can handle both delicate and heavy objects, achieving a balance between compliance and strength. Another significant contribution is the Flexible Robust Observant Gripper (FROG), which combines compliance and strong grasping force, leveraging feedforward grasp controllers and sensor feedback to effectively grasp a variety of objects, including fragile and heavy items.
Control Advances:
On the control side, we tackled the challenges of modeling and controlling hybrid robots with both soft and rigid components. Unlike previous works focused on serially structured robots, we addressed robots with intrinsically coupled elasticity between degrees of freedom. We developed a novel controller to compensate for elastic coupling in underactuated systems, proving stability using Lyapunov methods and validating its effectiveness through simulation and hardware experiments. Additionally, we advanced proprioceptive sensing for soft robots using machine learning to create accurate models of soft systems’ dynamics, enabling precise control in complex tasks.
Applications and Impact:
These innovations contribute to a growing ecosystem of robust, flexible robots capable of operating in diverse settings, from healthcare to manufacturing. The hands and manipulators designed in this project are capable of handling delicate and heavy objects, addressing real-world challenges in grasping and manipulation. Furthermore, the sensing and control methodologies developed here lay the groundwork for new approaches in soft robotics, bridging the gap between compliant and rigid systems while advancing the capabilities of hybrid robots for dynamic and interactive environments.
Last Modified: 12/10/2024
Modified by: Daniela Rus
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