Path following of field-tracked robots based on model predictive control with visual-inertial odometry and identified state-space dynamic model

Chun-Ting Sung; Wen-Chuan Tseng; Meng-Hui Hsu; Shean-Jen Chen

doi:10.1117/12.2619458

17 May 2022 Path following of field-tracked robots based on model predictive control with visual-inertial odometry and identified state-space dynamic model

Chun-Ting Sung, Wen-Chuan Tseng, Meng-Hui Hsu, Shean-Jen Chen

Author Affiliations +

Proceedings Volume 12138, Optics, Photonics and Digital Technologies for Imaging Applications VII; 121380K (2022) https://doi.org/10.1117/12.2619458
Event: SPIE Photonics Europe, 2022, Strasbourg, France

Abstract

Model predictive control (MPC) with prediction and control horizons under multivariable constraints can prompt field tracked vehicles to follow the reference path accurately. However, a kinematic model or a classic dynamic model of a vehicle is needed in MPC, and both of them must be linearized and hence the computation cost is large. Also, the parameters of a classic dynamic model are difficult to be measured. In this paper, system identification approach for estimated the linear state-space dynamic model of a field tracked vehicle in farm has been utilized. The dynamic model has been identified with more than 50% estimated fitting. Using the dynamic model, a linear MPC can be adopted, and hence the computation can be saved more than 2/3, compared with the conventional nonlinear MPC with a kinematic model. Furthermore, the tracked vehicle adopted the linear MPC with the dynamic model can achieve superior S-curve and L-shape path following.

Conference Presentation

Citation Download Citation

Chun-Ting Sung, Wen-Chuan Tseng, Meng-Hui Hsu, and Shean-Jen Chen "Path following of field-tracked robots based on model predictive control with visual-inertial odometry and identified state-space dynamic model", Proc. SPIE 12138, Optics, Photonics and Digital Technologies for Imaging Applications VII, 121380K (17 May 2022); https://doi.org/10.1117/12.2619458

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