@inproceedings{10d3b753f11f4891b43d62a5a12e8867,
title = "Trajectory Tracking Control with Estimated Driving Force for Tracked Vehicle Using Disturbance Observer and Machine Learning",
abstract = "This paper proposes a tracking control method that suppresses slippage by using the driving force of a tracked vehicle. First, the velocity of the tracked vehicle including slippage is estimated using a disturbance observer and machine learning technique. This estimated velocity is utilized to design an observer that can estimate the driving force of the crawler. By distributing and controlling the driving force, tracking control with reduced slippage can be realized. The experimental results demonstrate the tracking performance of the proposed control system.",
keywords = "Tracked vehicle, disturbance observer, driving force, machine learning, slippage, tracking control",
author = "Hiroaki Kuwahara and Toshiyuki Murakami",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 30th IEEE International Symposium on Industrial Electronics, ISIE 2021 ; Conference date: 20-06-2021 Through 23-06-2021",
year = "2021",
month = jun,
day = "20",
doi = "10.1109/ISIE45552.2021.9576259",
language = "English",
series = "IEEE International Symposium on Industrial Electronics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of 2021 IEEE 30th International Symposium on Industrial Electronics, ISIE 2021",
}