Abstract
This work presents a practical method of obtaining a dynamic system model for small omnidirectional aquatic vehicles. The models produced can be used to improve vehicle localisation, aid in the design or tuning of control systems and facilitate the development of simulated environments. The use of a dynamic model for onboard real-time velocity prediction is of particular importance for aquatic vehicles because, unlike ground vehicles, fast and direct measurement of velocity using encoders is not possible. Previous work on model identification of aquatic vehicles has focused on large vessels that are typically underactuated and have low controllability in the sway direction. In this paper it is demonstrated that the procedure for identifying the model coefficients can be performed quickly, without specialist equipment and using only onboard sensors. This is of key importance because the dynamic model coefficients will change with the payload. Two different thrust allocation schemes are tested, one of which is a known method and another is proposed here. Validation tests are performed and the models are shown to be suitable for their intended applications.
Significant reduction in model error is demonstrated using the novel thrust allocation method that is designed to avoid deadbands in the thruster responses.
Significant reduction in model error is demonstrated using the novel thrust allocation method that is designed to avoid deadbands in the thruster responses.
Original language | English |
---|---|
Number of pages | 6 |
Publication status | Published - 2020 |
Event | 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) - Duration: 25 Oct 2020 → … https://www.iros2020.org/ |
Conference
Conference | 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
---|---|
Abbreviated title | IROS |
Period | 25/10/20 → … |
Internet address |