Award Abstract # 2314560
Collaborative Research: Embedded Mechano-Intelligence for Soft Robotics

NSF Org: CMMI
Division of Civil, Mechanical, and Manufacturing Innovation
Recipient: REGENTS OF THE UNIVERSITY OF MICHIGAN
Initial Amendment Date: September 14, 2023
Latest Amendment Date: September 14, 2023
Award Number: 2314560
Award Instrument: Standard Grant
Program Manager: Jordan Berg
jberg@nsf.gov
 (703)292-5365
CMMI
 Division of Civil, Mechanical, and Manufacturing Innovation
ENG
 Directorate for Engineering
Start Date: September 1, 2023
End Date: August 31, 2026 (Estimated)
Total Intended Award Amount: $454,020.00
Total Awarded Amount to Date: $454,020.00
Funds Obligated to Date: FY 2023 = $454,020.00
History of Investigator:
  • Kon-Well Wang (Principal Investigator)
    kwwang@umich.edu
Recipient Sponsored Research Office: Regents of the University of Michigan - Ann Arbor
1109 GEDDES AVE STE 3300
ANN ARBOR
MI  US  48109-1015
(734)763-6438
Sponsor Congressional District: 06
Primary Place of Performance: Regents of the University of Michigan - Ann Arbor
503 THOMPSON ST
ANN ARBOR
MI  US  48109-1340
Primary Place of Performance
Congressional District:
06
Unique Entity Identifier (UEI): GNJ7BBP73WE9
Parent UEI:
NSF Program(s): FRR-Foundationl Rsrch Robotics,
FRR-Foundationl Rsrch Robotics
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 6840
Program Element Code(s): 144y00, 144Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

This collaborative Foundational Research in Robotics (FRR) project will create soft materials with integrated sensors, interconnections, logic circuits, and actuators. These materials will enable the development of soft robots with perception, processing, and responsiveness distributed throughout their structures. These capabilities will be demonstrated by a soft robotic platform that can recognize and sort simple objects by their shape, size, and weight, using only these novel materials and without requiring any additional sensing or computing. This soft material-based manipulator will be the first step towards a new class of soft robotic components that can coordinate and intelligently engage with objects in their environment, for a range of practical purposes. Such devices represent a major step for the field of soft robotics and will broadly advance the future of motion control systems, autonomous haptic devices, self-aware sensor-actuator networks, and more. Potential impacts may be felt in societally important application areas such as manufacturing, transportation, and biomedical devices. The research will be coupled with an extensive outreach, education, and mentoring program that integrates the research concepts into classroom and engagement activities among multiple diverse student groups.

The research goal of this project is to establish a fundamental synthesis of material and functional components in soft matter to embody intelligence, endowing robots with new capabilities that will significantly enhance their autonomy as compared to the current systems that heavily depend on add-on hardware. The new system will require less electric power and have faster reactions and better survivability than current systems. This project will culminate in a soft robotic sorting manipulator that autonomously detects physical characteristics of items and positions those items into proximity with objects having similar features. This goal will be achieved by a novel integration of embedded mechano-intelligence and field-responsive polymers. Together, these constituents will process information regarding item shape and weight and will trigger reconfiguration of the manipulator so as to position the items into distinct categories. By requiring only a low-voltage input to function, the embedded mechano-intelligence employs only the necessary computational power and eliminates conventional controllers and failure-prone electrical wiring in soft materials. The field-responsive polymers will be used in conjunction with principles of elastic stability theory to minimize the actuating authority required to reconfigure the load-bearing manipulator.

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.

Please report errors in award information by writing to: awardsearch@nsf.gov.

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