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Underactuation is a core challenge associated with controlling soft and continuum robots, which possess theoretically infinite degrees of freedom, but few actuators. However, m actuators may still be used to control a dynamic soft robot in an m-dimensional output task space. In this paper we develop a task-space control approach for planar continuum robots that is robust to modeling error and requires very little sensor information. The controller is based on a highly underactuated discrete rod mechanics model in maximal coordinates and does not require conversion to a classical robot dynamics model form. This promotes straightforward control design, implementation and efficiency. We perform input-output feedback linearization on this model, apply sliding mode control to increase robustness, and formulate an observer to estimate the full state from sparse output measurements. Simulation results show exact task-space reference tracking behavior can be achieved even in the presence of significant modeling error, inaccurate initial conditions, and output-only sensing.
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A New Approach to Model Constant Curvature Continuum Robot Dynamics
Abstract Inspired by nature, continuum robots show their potential in human-centered environments due to the compliant-to-obstacle features and dexterous mobility. However, there are few such robots successfully implemented outside the laboratory so far. One reason is believed to be due to the real time control challenge for soft robots, which require a highly efficient, highly accurate dynamic model. This paper presents a new systematic methodology to formulate the dynamics of constant curvature continuum robots. The new approach builds on several new techniques: 1) using the virtual work principle to formulate the equation of motion, 2) using specifically selected kinematic representations to separate integral variables from the non-integral variables, and 3) using vector representations to put the integral in a compact form. By doing so, the hard-to-solve integrals are evaluated analytically in advance and the accurate inverse dynamics are established accordingly. Numerical simulations are conducted to evaluate the performances of the newly proposed model.
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- Award ID(s):
- 1906727
- PAR ID:
- 10155506
- Date Published:
- Journal Name:
- ASME 2019 Dynamic Systems and Control Conference
- Volume:
- 3
- Page Range / eLocation ID:
- V003T20A001
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1115/DSCC2019-8999
