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Massachusetts Institute of Technology

Enhancing the Performance of Skeletal Muscle Powered Biohybrid Robots

Abstract

dc:description.abstract

Skeletal muscle powers all voluntary motion in many living creatures, enabling behaviors such as walking, jumping, swimming, and flying. The field of biohybrid robotics aims to use biological actuators, such as skeletal muscle, to power adaptable robots that respond to their environment. Previous work in this field has focused on deploying 3D skeletal muscle tissues to power robotic function. In natural systems, muscles can also be organized in 2D formats to power a range of movements such as fish-like swimming and peristaltic pumping. However, long-lasting 2D cultures of skeletal muscle have been precluded by force-generating cells delaminating from their underlying substrate. Building on previous work from our lab demonstrating a method to culture contractile skeletal muscle in 2D formats, this work aims to enhance the performance of these systems by tuning substrate stiffness and topography. We show that optimizing system parameters prolongs actuator lifetime and enhances force by 100x.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2025

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Bawa, Maheera
Advisor dc:contributor.advisor
  • Raman, Ritu

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright retained by author(s)

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/163453
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/163453

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Bawa, Maheera. Enhancing the Performance of Skeletal Muscle Powered Biohybrid Robots. Massachusetts Institute of Technology, 2025. https://hdl.handle.net/1721.1/163453