Data-driven control of planar snake robot locomotion
File(s)
Accepted version
Author(s)
Scarpa, Maria Luisa
Nortmann, Benita
Pettersen, Kristin Y
Mylvaganam, Thulasi
Type
Conference Paper
Abstract
A direct data-driven strategy for snake-robot lo-
comotion control is proposed in this paper. The approach leads
to a time-varying state feedback controller with robustness
guarantees. Instead of relying on exact model knowledge -
which is often not available in practice - the proposed control
strategy requires only input-state data collected during offline
experiments. The efficacy of the proposed strategy is demon-
strated via simulations. Notably, by using data to compensate
for inaccurate models, the proposed control strategy can lead
to significant improvements in closed-loop performance com-
pared to existing (model-based) control strategies, while also
eliminating the need for manual tuning of control parameters.
comotion control is proposed in this paper. The approach leads
to a time-varying state feedback controller with robustness
guarantees. Instead of relying on exact model knowledge -
which is often not available in practice - the proposed control
strategy requires only input-state data collected during offline
experiments. The efficacy of the proposed strategy is demon-
strated via simulations. Notably, by using data to compensate
for inaccurate models, the proposed control strategy can lead
to significant improvements in closed-loop performance com-
pared to existing (model-based) control strategies, while also
eliminating the need for manual tuning of control parameters.
Date Issued
2023-01-10
Date Acceptance
2022-07-15
Citation
2022 IEEE 61st Conference on Decision and Control (CDC), 2023
Publisher
IEEE
Journal / Book Title
2022 IEEE 61st Conference on Decision and Control (CDC)
Copyright Statement
Copyright © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Source
61st IEEE Conference on Decision and Control
Publication Status
Published
Finish Date
2022-12-09
Coverage Spatial
Cancun, Mexico