Linear Parameter-Varying Dynamic Modeling of Agricultural Robots on Variable-Friction Soils

Accacio F.dos Santos Neto; Marcelo R. Petry; Antonio Paulo Moreira; Paolo Mercorelli

doi:10.1109/ICARA69401.2026.11480330

Linear Parameter-Varying Dynamic Modeling of Agricultural Robots on Variable-Friction Soils

Accacio F.dos Santos Neto
, Marcelo R. Petry
, Antonio Paulo Moreira
, Paolo Mercorelli

Professorship of Control and Drive Systems

Research output: Journal contributions › Conference article in journal › Research › peer-review

Abstract

Accurate dynamic modeling of ground robots (Unmanned Ground Vehicles - UGVs) is essential for robust control and navigation in agricultural environments, where variations in soil friction and rolling resistance significantly affect system dynamics. This work proposes a Linear Parameter-Varying (LPV) model parameterized by the friction coefficient, identified under different soil conditions using two excitation strategies: Amplitude-Pseudo-Random Binary Sequence (APRBS) and standard maneuvers (SM). A simulated ground robot - the Clearpath Husky - was used under multiple soil friction scenarios within the ROS 2 and Gazebo simulation environment. The results show that the LPV model effectively captures the influence of soil friction, with both LPV APRBS and LPV SM yielding similar RMSE values across scenarios. The results also highlight the feasibility of using SM-based excitation for identifying the robot dynamics.

Original language	English
Journal	Proceedings of the International Conference on Automation, Robotics and Applications, ICARA
Issue number	2026
Pages (from-to)	222-227
Number of pages	6
ISSN	2767-7737
DOIs	https://doi.org/10.1109/ICARA69401.2026.11480330
Publication status	Published - 2026
Event	12th International Conference on Automation, Robotics and Applications - ICARA 2026 - Istanbul, Istanbul, Turkey, Istanbul, Turkey Duration: 05.02.2026 → 07.02.2026 Conference number: 12 http://www.icara.us/ (Official Event Website) https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=11480269 (Proceedings URL) https://doi.org/10.1109/icara69401.2026 (DOI)

Bibliographical note

Publisher Copyright:
© 2026 IEEE.

Research areas and keywords

agricultural robotics
friction variation
Gazebo Simulator
LPV modeling
parameter identification
UGV
Engineering

ASJC Scopus Subject Areas

Modelling and Simulation
Safety, Risk, Reliability and Quality
Mechanical Engineering
Computer Science Applications
Control and Optimization
Artificial Intelligence

Access to Document

10.1109/ICARA69401.2026.11480330

Cite this

@article{758909e56ea247d280cef37b5f919133,

title = "Linear Parameter-Varying Dynamic Modeling of Agricultural Robots on Variable-Friction Soils",

abstract = "Accurate dynamic modeling of ground robots (Unmanned Ground Vehicles - UGVs) is essential for robust control and navigation in agricultural environments, where variations in soil friction and rolling resistance significantly affect system dynamics. This work proposes a Linear Parameter-Varying (LPV) model parameterized by the friction coefficient, identified under different soil conditions using two excitation strategies: Amplitude-Pseudo-Random Binary Sequence (APRBS) and standard maneuvers (SM). A simulated ground robot - the Clearpath Husky - was used under multiple soil friction scenarios within the ROS 2 and Gazebo simulation environment. The results show that the LPV model effectively captures the influence of soil friction, with both LPV APRBS and LPV SM yielding similar RMSE values across scenarios. The results also highlight the feasibility of using SM-based excitation for identifying the robot dynamics.",

keywords = "agricultural robotics, friction variation, Gazebo Simulator, LPV modeling, parameter identification, UGV, Engineering",

author = "Neto, \{Accacio F.dos Santos\} and Petry, \{Marcelo R.\} and Moreira, \{Antonio Paulo\} and Paolo Mercorelli",

note = "Publisher Copyright: {\textcopyright} 2026 IEEE.; 12th International Conference on Automation, Robotics and Applications - ICARA 2026, ICARA 2026 ; Conference date: 05-02-2026 Through 07-02-2026",

year = "2026",

doi = "10.1109/ICARA69401.2026.11480330",

language = "English",

pages = "222--227",

journal = "Proceedings of the International Conference on Automation, Robotics and Applications, ICARA",

issn = "2767-7737",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

number = "2026",

url = "http://www.icara.us/, https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=11480269, https://doi.org/10.1109/icara69401.2026",

}

Linear Parameter-Varying Dynamic Modeling of Agricultural Robots on Variable-Friction Soils. / Neto, Accacio F.dos Santos; Petry, Marcelo R.; Moreira, Antonio Paulo et al.
In: Proceedings of the International Conference on Automation, Robotics and Applications, ICARA, No. 2026, 2026, p. 222-227.

Research output: Journal contributions › Conference article in journal › Research › peer-review

TY - JOUR

T1 - Linear Parameter-Varying Dynamic Modeling of Agricultural Robots on Variable-Friction Soils

AU - Neto, Accacio F.dos Santos

AU - Petry, Marcelo R.

AU - Moreira, Antonio Paulo

AU - Mercorelli, Paolo

N1 - Conference code: 12

PY - 2026

Y1 - 2026

N2 - Accurate dynamic modeling of ground robots (Unmanned Ground Vehicles - UGVs) is essential for robust control and navigation in agricultural environments, where variations in soil friction and rolling resistance significantly affect system dynamics. This work proposes a Linear Parameter-Varying (LPV) model parameterized by the friction coefficient, identified under different soil conditions using two excitation strategies: Amplitude-Pseudo-Random Binary Sequence (APRBS) and standard maneuvers (SM). A simulated ground robot - the Clearpath Husky - was used under multiple soil friction scenarios within the ROS 2 and Gazebo simulation environment. The results show that the LPV model effectively captures the influence of soil friction, with both LPV APRBS and LPV SM yielding similar RMSE values across scenarios. The results also highlight the feasibility of using SM-based excitation for identifying the robot dynamics.

AB - Accurate dynamic modeling of ground robots (Unmanned Ground Vehicles - UGVs) is essential for robust control and navigation in agricultural environments, where variations in soil friction and rolling resistance significantly affect system dynamics. This work proposes a Linear Parameter-Varying (LPV) model parameterized by the friction coefficient, identified under different soil conditions using two excitation strategies: Amplitude-Pseudo-Random Binary Sequence (APRBS) and standard maneuvers (SM). A simulated ground robot - the Clearpath Husky - was used under multiple soil friction scenarios within the ROS 2 and Gazebo simulation environment. The results show that the LPV model effectively captures the influence of soil friction, with both LPV APRBS and LPV SM yielding similar RMSE values across scenarios. The results also highlight the feasibility of using SM-based excitation for identifying the robot dynamics.

KW - agricultural robotics

KW - friction variation

KW - Gazebo Simulator

KW - LPV modeling

KW - parameter identification

KW - UGV

KW - Engineering

UR - https://www.scopus.com/pages/publications/105037849099

U2 - 10.1109/ICARA69401.2026.11480330

DO - 10.1109/ICARA69401.2026.11480330

M3 - Conference article in journal

AN - SCOPUS:105037849099

SN - 2767-7737

SP - 222

EP - 227

JO - Proceedings of the International Conference on Automation, Robotics and Applications, ICARA

JF - Proceedings of the International Conference on Automation, Robotics and Applications, ICARA

IS - 2026

T2 - 12th International Conference on Automation, Robotics and Applications - ICARA 2026

Y2 - 5 February 2026 through 7 February 2026

ER -

Linear Parameter-Varying Dynamic Modeling of Agricultural Robots on Variable-Friction Soils

Abstract

Bibliographical note

Research areas and keywords

ASJC Scopus Subject Areas

Access to Document

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Cite this