University of Illinois Urbana-Champaign

Learning-based control of a cyberoctopus

Shih, Chia-Hsien

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https://hdl.handle.net/2142/127317

Description

Title
Learning-based control of a cyberoctopus
Author(s)
Shih, Chia-Hsien
Issue Date
2024-09-04
Director of Research (if dissertation) or Advisor (if thesis)
Gazzola, Mattia
Doctoral Committee Chair(s)
Gazzola, Mattia
Committee Member(s)
  • Mehta, Prashant
  • Krishnan, Girish
  • Chowdhary, Girish
Department of Study
Mechanical Sci & Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
  • learning-based control
  • octopus-inspired robotics
  • hierarchical decompositioin
  • motion primitives
  • soft robot manipulation
  • soft robot locomotion
  • multi-arm coordination
Abstract
Inspired by the remarkable capabilities of octopuses, my work focuses on designing control strategies for a simulated soft-bodied octopus-like robot, the CyberOctopus. The continuous deformation and intricate mechanics of soft arms pose challenges in developing dynamic control models, especially when engaging with moving objects or coordinating multiple arms. Additionally, existing studies on soft arm manipulation have primarily focused on end-effectors, leaving whole-arm manipulation largely unexplored. To address these challenges, my research employs a hierarchical framework with static and dynamic activation strategies, leveraging the inherent mechanical intelligence of the arms to facilitate whole-arm interactions with other arms, obstacles, and moving objects in the environment. The CyberOctopus demonstrates refined manipulation and locomotion tasks in real-time, with potential applications in underwater exploration, search and rescue operations, and manufacturing processes.
Graduation Semester
2024-12
Type of Resource
Thesis
Handle URL
https://hdl.handle.net/2142/127317
Copyright and License Information
Copyright 2024 Chia-Hsien Shih

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