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Sangbae Kim. Estrada, Matthew A Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering 2012-10-26T18:08:52Z 2012-10-26T18:08:52Z 2012 2012 http://hdl.handle.net/1721.1/74436 813136389 Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012. Cataloged from PDF version of thesis. Includes bibliographical references (p. 39-40). This thesis illustrates the fabrication and characterization of a footpad based on an original principle of volumetric displacement sensing. It is intended for use in detecting ground reaction forces in a running quadrupedal robot. The footpad is manufactured as a monolithic, composite structure composed of multi-graded polymers reinforced by glass fiber to increase durability and traction. The volumetric displacement sensing principle utilizes a hyperelastic gel-like pad with embedded magnets and Hall-effect sensors. Normal and shear forces can be detected as contact forces cause the gel-like pad to deform into rigid wells without the need to expose the sensor. A one-time training process using an artificial neural network was used to relate the normal and shear forces with the volumetric displacement sensor output. Two iterations on geometry are prototyped and tested. The first shows the ability to accurately predict normal forces in the Z-axis up to 80 N with a root mean squared error of 6% but little information about shear forces in the X an Y-axis. The second iteration demonstrates an ability to pick up the presence and direction of shear forces up to 40 N but with a root mean squared error of 70%. This project demonstrates a proof-of-concept for a more robust force sensor suitable for use in robotics that requires compliance while interacting with its environment. by Matthew A. Estrada. S.B. 40 p. eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Mechanical Engineering. Design and fabrication of force sensing robotic foot utilizing the volumetric displacement of a hyperelastic polymer Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="53a918a7-2b96-411c-aeca-9679778def6c"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Design and fabrication of force sensing robotic foot utilizing the volumetric displacement of a hyperelastic polymer</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2012</PublicationDate> <Authors> <Author> <DisplayName>Estrada, Matthew A</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Mechanical Engineering.</Keyword> <Abstract>This thesis illustrates the fabrication and characterization of a footpad based on an original principle of volumetric displacement sensing. It is intended for use in detecting ground reaction forces in a running quadrupedal robot. The footpad is manufactured as a monolithic, composite structure composed of multi-graded polymers reinforced by glass fiber to increase durability and traction. The volumetric displacement sensing principle utilizes a hyperelastic gel-like pad with embedded magnets and Hall-effect sensors. Normal and shear forces can be detected as contact forces cause the gel-like pad to deform into rigid wells without the need to expose the sensor. A one-time training process using an artificial neural network was used to relate the normal and shear forces with the volumetric displacement sensor output. Two iterations on geometry are prototyped and tested. The first shows the ability to accurately predict normal forces in the Z-axis up to 80 N with a root mean squared error of 6% but little information about shear forces in the X an Y-axis. The second iteration demonstrates an ability to pick up the presence and direction of shear forces up to 40 N but with a root mean squared error of 70%. This project demonstrates a proof-of-concept for a more robust force sensor suitable for use in robotics that requires compliance while interacting with its environment.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>