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Massachusetts Institute of Technology

Incorporating High-Resolution Tactile Perception for Performative and Generalized Robotic Manipulation Through Compliance Estimation and Hardware Design

Abstract

dc:description.abstract

In robotics, replicating the natural proficiency with which humans perform manipulation tasks has proven challenging. Modern control schemes are predominantly learning-based and thus depend heavily on data collected via teleoperated demonstrations. Humans rely on our tactile perception to perform contact-rich and dynamic manipulation tasks. By more seamlessly incorporating high-resolution tactile sensing and haptic feedback into teleoperation interfaces, we can work to create stronger demonstration data to support the development of more effective learned control policies. In this thesis, we present two contributions toward this goal. First, we develop an algorithm to estimate the compliance of grasped objects in real-time from tactile images to provide haptic feedback to remote users. This algorithm combines both analytical and learning-based approaches to better generalize across both object shapes and materials. Second, we create a 1-DoF robotic gripper design with integrated tactile sensing. Inspired by the principle of self-similarity, this gripper is designed to better conform to complex object geometries than traditional designs and more securely grasp objects of many shapes and sizes. Together, these contributions can be utilized to create robust, tactile-aware teleoperation platforms. These platforms would facilitate more effective data collection and thereby promote the development of more performative autonomous action in generalized robotic manipulation scenarios.

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
  • Burgess, Michael
Advisor dc:contributor.advisor
  • Adelson, Edward H.

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/1721.1/163430
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/163430

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

Burgess, Michael. Incorporating High-Resolution Tactile Perception for Performative and Generalized Robotic Manipulation Through Compliance Estimation and Hardware Design. Massachusetts Institute of Technology, 2025. https://hdl.handle.net/1721.1/163430