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  5. Model Based Force Estimation and Stiffness Control for Continuum Robots
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Model Based Force Estimation and Stiffness Control for Continuum Robots

Date Issued
May 1, 2022
Author(s)
Aloi, Vincent A
Advisor(s)
Caleb D. Rucker
Additional Advisor(s)
William R. Hamel
Eric J. Barth
Jindong Tan
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/28376
Abstract

Continuum Robots are bio-inspired structures that mimic the motion of snakes, elephant trunks, octopus tentacles, etc. With good design, these robots can be naturally compliant and miniaturizable, which makes Continuum Robots ideal for traversing narrow complex environments. Their flexible design, however, prevents us from using traditional methods for controlling and estimating loading on rigid link robots.


In the first thrust of this research, we provided a novel stiffness control law that alters the behavior of an end effector during contact. This controller is applicable to any continuum robot where a method for sensing or estimating tip forces and pose exists. Using an integral approach, the control law is be capable of dictating different stiffness in multiple directions, both increase and decrease the stiffness of the end effector, as well as handle contacts with both rigid and compliant environments. An example of implementation is provided for a parallel continuum robot.

In the second thrust of this research, we introduce a general 3D load estimation approach that can be applied to any continuum robot with an existing kinetostatic model that maps actuation and externally applied loads into a robot pose. This method uses numerical minimization to predict a load distribution that will fit a robot model predicted shape to a directly sensed shape. Validation was preformed on a passive steel rod, a single degree of freedom tendon robot, and a two degree of freedom tendon robot.

Subjects

continuum robotics

robotics

control systems

force estimation

nonlinear optimizatio...

Disciplines
Applied Mechanics
Control Theory
Numerical Analysis and Computation
Robotics
Degree
Doctor of Philosophy
Major
Mechanical Engineering
File(s)
Thumbnail Image
Name

my_dissertation.pdf

Size

17.09 MB

Format

Adobe PDF

Checksum (MD5)

b42717340f0605f18a667b557b91953a

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